diff --git a/.circleci/config.yml b/.circleci/config.yml
index 5bcd6520..dcb2f03f 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -6,7 +6,7 @@ jobs:
     steps:
       - checkout
       - run: mkdir -p /tmp/coverage && mkdir -p /tmp/test_results
-      - run: pip3 install -e .[dev]
+      - run: pip3 install .
       - run: 
           name: Test
           command: pytest -vv tests
diff --git a/.gitignore b/.gitignore
index c778b7d9..f65ce068 100644
--- a/.gitignore
+++ b/.gitignore
@@ -8,6 +8,8 @@ dev_notes
 !tests/deep_mlp/end_to_end.ipynb
 *.egg*
 worktree/
+build/
+dist/
 # tests
 .pytest_cache
 tests/*/cpp
diff --git a/MANIFEST.in b/MANIFEST.in
index 5bf45efe..15362a77 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,2 +1,2 @@
 include LICENSE README.md
-recursive-include utensor_cgen/backend/snippets/templates *
+recursive-include utensor_cgen/backend/utensor/snippets/templates *
diff --git a/Makefile b/Makefile
index 804d8296..6eb2e9ee 100644
--- a/Makefile
+++ b/Makefile
@@ -3,7 +3,7 @@
 tests:
 	rm -f tests_log.txt
 	make test_utils test_ir test_transformer test_frontend \
-		test_matcher test_graph_constructor
+		test_matcher test_graph_constructor test_backend
 
 test_%:
 	@if [ -d .venv ]; then \
@@ -12,5 +12,23 @@ test_%:
 	 	 pytest tests/$@ -vv -s | tee -a tests_log.txt; \
 	 fi;
 
+package:
+	rm -rf dist/*
+	.venv/bin/python setup.py bdist_wheel sdist
+	rm -rf build utensor_cgen.egg-info/
+
+upload-test: package
+	.venv/bin/twine upload -r pypitest dist/*
+
+install-test: package
+	pip uninstall -y utensor-cgen
+	pip install dist/*.tar.gz
+
+upload: package
+	.venv/bin/twine upload -r pypi dist/*
+
 clean:
-	rm -rf tests_log.txt *.pdf .pytest_cache
+	rm -rf tests_log.txt *.pdf \
+	models data \
+	tests/test_backend/{models,data} \
+	.pytest_cache dist/ build/
diff --git a/Pipfile.lock b/Pipfile.lock
index d94bc386..403da44e 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -16,23 +16,23 @@
     "default": {
         "absl-py": {
             "hashes": [
-                "sha256:b943d1c567743ed0455878fcd60bc28ac9fae38d129d1ccfad58079da00b8951"
+                "sha256:75e737d6ce7723d9ff9b7aa1ba3233c34be62ef18d5859e706b8fdc828989830"
             ],
-            "version": "==0.7.1"
+            "version": "==0.9.0"
         },
         "astor": {
             "hashes": [
-                "sha256:0e41295809baf43ae8303350e031aff81ae52189b6f881f36d623fa8b2f1960e",
-                "sha256:37a6eed8b371f1228db08234ed7f6cfdc7817a3ed3824797e20cbb11dc2a7862"
+                "sha256:070a54e890cefb5b3739d19f30f5a5ec840ffc9c50ffa7d23cc9fc1a38ebbfc5",
+                "sha256:6a6effda93f4e1ce9f618779b2dd1d9d84f1e32812c23a29b3fff6fd7f63fa5e"
             ],
-            "version": "==0.8.0"
+            "version": "==0.8.1"
         },
         "attrs": {
             "hashes": [
-                "sha256:69c0dbf2ed392de1cb5ec704444b08a5ef81680a61cb899dc08127123af36a79",
-                "sha256:f0b870f674851ecbfbbbd364d6b5cbdff9dcedbc7f3f5e18a6891057f21fe399"
+                "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c",
+                "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"
             ],
-            "version": "==19.1.0"
+            "version": "==19.3.0"
         },
         "click": {
             "hashes": [
@@ -47,79 +47,98 @@
         },
         "gast": {
             "hashes": [
-                "sha256:fe939df4583692f0512161ec1c880e0a10e71e6a232da045ab8edd3756fbadf0"
+                "sha256:5c7617f1f6c8b8b426819642b16b9016727ddaecd16af9a07753e537eba8a3a5"
             ],
-            "version": "==0.2.2"
+            "version": "==0.3.2"
+        },
+        "graphviz": {
+            "hashes": [
+                "sha256:241fb099e32b8e8c2acca747211c8237e40c0b89f24b1622860075d59f4c4b25",
+                "sha256:60acbeee346e8c14555821eab57dbf68a169e6c10bce40e83c1bf44f63a62a01"
+            ],
+            "version": "==0.13.2"
         },
         "grpcio": {
             "hashes": [
-                "sha256:03b78b4e7dcdfe3e257bb528cc93923f9cbbab6d5babf15a60d21e9a4a70b1a2",
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-                "sha256:22e167a9406d73dd19ffe8ed6a485f17e6eac82505be8c108897f15e68badcbb",
-                "sha256:31d0aeca8d8ee2301c62c5c340e0889d653b1280d68f9fa203982cb6337b050e",
-                "sha256:44c7f99ca17ebbcc96fc54ed00b454d8313f1eac28c563098d8b901025aff941",
-                "sha256:5471444f53f9db6a1f1f11f5dbc173228881df8446380b6b98f90afb8fd8348e",
-                "sha256:561bca3b1bde6d6564306eb05848fd155136e9c3a25d2961129b1e2edba22fce",
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-                "sha256:8805d486c6128cc0fcc8ecf16c4095d99a8693a541ef851429ab334e028a4a97",
-                "sha256:8d71b7a89c306a41ccc7741fc9409b14f5b86727455c2a1c0c7cfcb0f784e1f2",
-                "sha256:9e1b80bd65f8f160880cb4dad7f55697f6d37b2d7f251fc0c2128e811928f369",
-                "sha256:9e290c84a145ae2411ee0ec9913c41cd7500e2e7485fe93632434d84ef4fda67",
-                "sha256:9ec9f88b5bc94bd99372f27cdd53af1c92ba06717380b127733b953cfb181174",
-                "sha256:a0a02a8b4ba6deadf706d5f849539b3685b72b186a3c9ef5d43e8972ed60fb6f",
-                "sha256:a4059c59519f5940e01a071f74ae2a60ea8f6185b03d22a09d40c7959a36b16b",
-                "sha256:a6e028c2a6da2ebfa2365a5b32531d311fbfec0e3600fc27e901b64f0ff7e54e",
-                "sha256:adcdebf9f8463df4120c427cf6c9aed39258bccd03ed37b6939e7a145d64d6e0",
-                "sha256:bdec982610259d07156a58f80b8c3e69be7751a9208bc577b059c5193d087fad",
-                "sha256:cefc4d4251ffb73feb303d4b7e9d6c367cb60f2db16d259ea28b114045f965aa",
-                "sha256:d4145c8aa6afbac10ad27e408f7ce15992fe89ba5d0b4abca31c0c2729864c03",
-                "sha256:da76dc5ad719ee99de5ea28a5629ff92172cbb4a70d8a6ae3a5b7a53c7382ce1",
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-            ],
-            "version": "==1.22.0"
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+                "sha256:1cf710c04689daa5cc1e598efba00b028215700dcc1bf66fcb7b4f64f2ea5d5f",
+                "sha256:2da5cee9faf17bb8daf500cd0d28a17ae881ab5500f070a6aace457f4c08cac4",
+                "sha256:2f78ebf340eaf28fa09aba0f836a8b869af1716078dfe8f3b3f6ff785d8f2b0f",
+                "sha256:33a07a1a8e817d733588dbd18e567caad1a6fe0d440c165619866cd490c7911a",
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+                "sha256:bdb2f3dcb664f0c39ef1312cd6acf6bc6375252e4420cf8f36fff4cb4fa55c71",
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+                "sha256:d1a481777952e4f99b8a6956581f3ee866d7614100d70ae6d7e07327570b85ce",
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+                "sha256:d7e5b7af1350e9c8c17a7baf99d575fbd2de69f7f0b0e6ebd47b57506de6493a",
+                "sha256:d9542366a0917b9b48bab1fee481ac01f56bdffc52437b598c09e7840148a6a9",
+                "sha256:df7cdfb40179acc9790a462c049e0b8e109481164dd7ad1a388dd67ff1528759",
+                "sha256:e1a9d9d2e7224d981aea8da79260c7f6932bf31ce1f99b7ccfa5eceeb30dc5d0",
+                "sha256:ed10e5fad105ecb0b12822f924e62d0deb07f46683a0b64416b17fd143daba1d",
+                "sha256:f0ec5371ce2363b03531ed522bfbe691ec940f51f0e111f0500fc0f44518c69d",
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+                "sha256:ffec45b0db18a555fdfe0c6fa2d0a3fceb751b22b31e8fcd14ceed7bde05481e"
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+            "version": "==1.26.0"
         },
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-            "version": "==2.9.0"
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@@ -129,10 +148,10 @@
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@@ -197,131 +216,142 @@
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+                "sha256:a2e6f57114933882ec701807f217df2fb4588d47f71f227c0a163446b930d507",
+                "sha256:a6b970a2eccfcbabe1acf230fbf112face1c4700036c95e195f3554d7bcb04c1",
+                "sha256:bc45641cbcdea068b67438244c926f9fd3e5cbdd824448a4a64370610df7c593",
+                "sha256:d61b14a9090da77fe87e38ba4c6c43d3533dcbeb5d84f5474e7ac63c532dcc9c",
+                "sha256:d6faf5dbefb593e127463f58076b62fcfe0784187be8fe1aa9167388f24a22a1"
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+            "version": "==3.11.2"
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         "pyyaml": {
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-            "version": "==5.1.2"
+                "sha256:0e7f69397d53155e55d10ff68fdfb2cf630a35e6daf65cf0bdeaf04f127c09dc",
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+                "sha256:4b6be5edb9f6bb73680f5bf4ee08ff25416d1400fbd4535fe0069b2994da07cd",
+                "sha256:7f38e35c00e160db592091751d385cd7b3046d6d51f578b29943225178257b31",
+                "sha256:8100c896ecb361794d8bfdb9c11fce618c7cf83d624d73d5ab38aef3bc82d43f",
+                "sha256:c0ee8eca2c582d29c3c2ec6e2c4f703d1b7f1fb10bc72317355a746057e7346c",
+                "sha256:e4c015484ff0ff197564917b4b4246ca03f411b9bd7f16e02a2f586eb48b6d04",
+                "sha256:ebc4ed52dcc93eeebeae5cf5deb2ae4347b3a81c3fa12b0b8c976544829396a4"
+            ],
+            "version": "==5.2"
         },
         "six": {
             "hashes": [
-                "sha256:3350809f0555b11f552448330d0b52d5f24c91a322ea4a15ef22629740f3761c",
-                "sha256:d16a0141ec1a18405cd4ce8b4613101da75da0e9a7aec5bdd4fa804d0e0eba73"
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+                "sha256:30f610279e8b2578cab6db20741130331735c781b56053c59c4076da27f06b66"
             ],
-            "version": "==1.12.0"
+            "version": "==1.13.0"
         },
         "tensorboard": {
             "hashes": [
@@ -362,62 +392,63 @@
             ],
             "version": "==1.1.0"
         },
-        "torch": {
+        "toml": {
             "hashes": [
-                "sha256:3f3023345c6db4db28a79f52ada186fc6307ba8a0c85252eb0a70b78eff3a443",
-                "sha256:87d4778e848e4c83505a0d10135d514871ea0ae2da75e0710be272ea5048f9e3",
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-                "sha256:ee2c48794c767606f4629ee3d1f147e2fcb1a02a31b6bca252cc7c7e3ad22c4a"
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+                "sha256:235682dd292d5899d361a811df37e04a8828a5b1da3115886b73cf81ebc9100e"
             ],
-            "version": "==1.1.0.post2"
+            "version": "==0.10.0"
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-        "torchvision": {
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-                "sha256:87fd98cd817cdb9ea5f0010a1b30eb0b297922e33a8c27cc940ed486044dc82c",
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-                "sha256:fb8ea1e2f9d40dbd61eafaadf302dd062df5c3793f74599692443fdee7f9707b"
+                "sha256:0cec2e13a2e95c24c34f17d437f354ee2a40902e8d515a524556b350e12555dd",
+                "sha256:134e8291a97151b1ffeea09cb9ddde5238beb4e6d9dfb66657143d6990bfb865",
+                "sha256:31062923ac2e60eac676f6a0ae14702b051c158bbcf7f440eaba266b0defa197",
+                "sha256:3b05233481b51bb636cee63dc761bb7f602e198178782ff4159d385d1759608b",
+                "sha256:458f1d87e5b7064b2c39e36675d84e163be3143dd2fc806057b7878880c461bc",
+                "sha256:72a1c85bffd2154f085bc0a1d378d8a54e55a57d49664b874fe7c949022bf071",
+                "sha256:77fd8866c0bf529861ffd850a5dada2190a8d9c5167719fb0cfa89163e23b143",
+                "sha256:b6f01d851d1c5989d4a99b50ae0187762b15b7718dcd1a33704b665daa2402f9",
+                "sha256:d8e1d904a6193ed14a4fed220b00503b2baa576e71471286d1ebba899c851fae"
             ],
-            "version": "==0.3.0"
+            "version": "==1.3.1"
         },
-        "typing": {
+        "torchvision": {
             "hashes": [
-                "sha256:38566c558a0a94d6531012c8e917b1b8518a41e418f7f15f00e129cc80162ad3",
-                "sha256:53765ec4f83a2b720214727e319607879fec4acde22c4fbb54fa2604e79e44ce",
-                "sha256:84698954b4e6719e912ef9a42a2431407fe3755590831699debda6fba92aac55"
+                "sha256:0f8245d6378acc86917f58492675f93df5279abae8bc5f832e3510722191f6c9",
+                "sha256:1ad7593d94f6612ccb84a59467f0d10cdc213fb3e2bb91f1e773eb844787fa4c",
+                "sha256:2553405b9afe3cedb410873b9877eb18b1526f8b01cb7c2747e51b69a936e0b5",
+                "sha256:276a385f2f5fe484bf08467b5d081d9144b97eb458ba5b4a11e4640389e53149",
+                "sha256:66deba9c577e36f4f071decdd894bf7ba794ac133dae64b3fd02fc3f0c6b989d",
+                "sha256:7a458330e4efcd66f9f70127ab21fcf8cfea84acda8e707322fd2843aa6dd396",
+                "sha256:8ff715c2323d9eca89126824ebfa74b282a95d6f64a4743fbe9b738d2de21c77",
+                "sha256:dca4aadc12a123730957b501f9c5c2870d2f6727a2c28552cb7907b68b0ea10c",
+                "sha256:dda25ce304978bba19e6543f7dcfee4f37d2f128ec83d4ab0c7e8f991d64865f"
             ],
-            "version": "==3.7.4"
+            "version": "==0.4.2"
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         "typing-extensions": {
             "hashes": [
-                "sha256:2ed632b30bb54fc3941c382decfd0ee4148f5c591651c9272473fea2c6397d95",
-                "sha256:b1edbbf0652660e32ae780ac9433f4231e7339c7f9a8057d0f042fcbcea49b87",
-                "sha256:d8179012ec2c620d3791ca6fe2bf7979d979acdbef1fca0bc56b37411db682ed"
+                "sha256:091ecc894d5e908ac75209f10d5b4f118fbdb2eb1ede6a63544054bb1edb41f2",
+                "sha256:910f4656f54de5993ad9304959ce9bb903f90aadc7c67a0bef07e678014e892d",
+                "sha256:cf8b63fedea4d89bab840ecbb93e75578af28f76f66c35889bd7065f5af88575"
             ],
-            "version": "==3.7.4"
+            "version": "==3.7.4.1"
         },
         "werkzeug": {
             "hashes": [
-                "sha256:87ae4e5b5366da2347eb3116c0e6c681a0e939a33b2805e2c0cbd282664932c4",
-                "sha256:a13b74dd3c45f758d4ebdb224be8f1ab8ef58b3c0ffc1783a8c7d9f4f50227e6"
+                "sha256:7280924747b5733b246fe23972186c6b348f9ae29724135a6dfc1e53cea433e7",
+                "sha256:e5f4a1f98b52b18a93da705a7458e55afb26f32bff83ff5d19189f92462d65c4"
             ],
-            "version": "==0.15.5"
+            "version": "==0.16.0"
         },
         "wheel": {
             "hashes": [
-                "sha256:5e79117472686ac0c4aef5bad5172ea73a1c2d1646b808c35926bd26bdfb0c08",
-                "sha256:62fcfa03d45b5b722539ccbc07b190e4bfff4bb9e3a4d470dd9f6a0981002565"
+                "sha256:10c9da68765315ed98850f8e048347c3eb06dd81822dc2ab1d4fde9dc9702646",
+                "sha256:f4da1763d3becf2e2cd92a14a7c920f0f00eca30fdde9ea992c836685b9faf28"
             ],
             "markers": "python_version >= '3'",
-            "version": "==0.33.4"
+            "version": "==0.33.6"
         }
     },
     "develop": {
@@ -430,25 +461,18 @@
         },
         "astroid": {
             "hashes": [
-                "sha256:6560e1e1749f68c64a4b5dee4e091fce798d2f0d84ebe638cf0e0585a343acf4",
-                "sha256:b65db1bbaac9f9f4d190199bb8680af6f6f84fd3769a5ea883df8a91fe68b4c4"
+                "sha256:71ea07f44df9568a75d0f354c49143a4575d90645e9fead6dfb52c26a85ed13a",
+                "sha256:840947ebfa8b58f318d42301cf8c0a20fd794a33b61cc4638e28e9e61ba32f42"
             ],
             "markers": "python_version >= '3'",
-            "version": "==2.2.5"
-        },
-        "atomicwrites": {
-            "hashes": [
-                "sha256:03472c30eb2c5d1ba9227e4c2ca66ab8287fbfbbda3888aa93dc2e28fc6811b4",
-                "sha256:75a9445bac02d8d058d5e1fe689654ba5a6556a1dfd8ce6ec55a0ed79866cfa6"
-            ],
-            "version": "==1.3.0"
+            "version": "==2.3.3"
         },
         "attrs": {
             "hashes": [
-                "sha256:69c0dbf2ed392de1cb5ec704444b08a5ef81680a61cb899dc08127123af36a79",
-                "sha256:f0b870f674851ecbfbbbd364d6b5cbdff9dcedbc7f3f5e18a6891057f21fe399"
+                "sha256:08a96c641c3a74e44eb59afb61a24f2cb9f4d7188748e76ba4bb5edfa3cb7d1c",
+                "sha256:f7b7ce16570fe9965acd6d30101a28f62fb4a7f9e926b3bbc9b61f8b04247e72"
             ],
-            "version": "==19.1.0"
+            "version": "==19.3.0"
         },
         "babel": {
             "hashes": [
@@ -459,10 +483,10 @@
         },
         "certifi": {
             "hashes": [
-                "sha256:046832c04d4e752f37383b628bc601a7ea7211496b4638f6514d0e5b9acc4939",
-                "sha256:945e3ba63a0b9f577b1395204e13c3a231f9bc0223888be653286534e5873695"
+                "sha256:017c25db2a153ce562900032d5bc68e9f191e44e9a0f762f373977de9df1fbb3",
+                "sha256:25b64c7da4cd7479594d035c08c2d809eb4aab3a26e5a990ea98cc450c320f1f"
             ],
-            "version": "==2019.6.16"
+            "version": "==2019.11.28"
         },
         "chardet": {
             "hashes": [
@@ -488,19 +512,18 @@
         },
         "flake8": {
             "hashes": [
-                "sha256:19241c1cbc971b9962473e4438a2ca19749a7dd002dd1a946eaba171b4114548",
-                "sha256:8e9dfa3cecb2400b3738a42c54c3043e821682b9c840b0448c0503f781130696"
+                "sha256:45681a117ecc81e870cbf1262835ae4af5e7a8b08e40b944a8a6e6b895914cfb",
+                "sha256:49356e766643ad15072a789a20915d3c91dc89fd313ccd71802303fd67e4deca"
             ],
             "index": "pypi",
-            "version": "==3.7.8"
+            "version": "==3.7.9"
         },
         "graphviz": {
             "hashes": [
-                "sha256:6d0f69c107cfdc9bd1df3763fad99569bbcba29d0c52ffcbc6f266621d8bf709",
-                "sha256:914b8b124942d82e3e1dcef499c9fe77c10acd3d18a1cfeeb2b9de05f6d24805"
+                "sha256:241fb099e32b8e8c2acca747211c8237e40c0b89f24b1622860075d59f4c4b25",
+                "sha256:60acbeee346e8c14555821eab57dbf68a169e6c10bce40e83c1bf44f63a62a01"
             ],
-            "index": "pypi",
-            "version": "==0.11.1"
+            "version": "==0.13.2"
         },
         "idna": {
             "hashes": [
@@ -518,10 +541,11 @@
         },
         "importlib-metadata": {
             "hashes": [
-                "sha256:23d3d873e008a513952355379d93cbcab874c58f4f034ff657c7a87422fa64e8",
-                "sha256:80d2de76188eabfbfcf27e6a37342c2827801e59c4cc14b0371c56fed43820e3"
+                "sha256:073a852570f92da5f744a3472af1b61e28e9f78ccf0c9117658dc32b15de7b45",
+                "sha256:d95141fbfa7ef2ec65cfd945e2af7e5a6ddbd7c8d9a25e66ff3be8e3daf9f60f"
             ],
-            "version": "==0.19"
+            "markers": "python_version < '3.8'",
+            "version": "==1.3.0"
         },
         "isort": {
             "hashes": [
@@ -532,33 +556,36 @@
         },
         "jinja2": {
             "hashes": [
-                "sha256:065c4f02ebe7f7cf559e49ee5a95fb800a9e4528727aec6f24402a5374c65013",
-                "sha256:14dd6caf1527abb21f08f86c784eac40853ba93edb79552aa1e4b8aef1b61c7b"
+                "sha256:74320bb91f31270f9551d46522e33af46a80c3d619f4a4bf42b3164d30b5911f",
+                "sha256:9fe95f19286cfefaa917656583d020be14e7859c6b0252588391e47db34527de"
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-            "version": "==2.10.1"
+            "version": "==2.10.3"
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         "lazy-object-proxy": {
             "hashes": [
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-                "sha256:23f63c0821cc96a23332e45dfaa83266feff8adc72b9bcaef86c202af765244f",
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-                "sha256:acce4e3267610c4fdb6632b3886fe3f2f7dd641158a843cf6b6a68e4ce81477b",
-                "sha256:be089bb6b83fac7f29d357b2dc4cf2b8eb8d98fe9d9ff89f9ea6012970a853c7",
-                "sha256:bfab710d859c779f273cc48fb86af38d6e9210f38287df0069a63e40b45a2f5c",
-                "sha256:c10d29019927301d524a22ced72706380de7cfc50f767217485a912b4c8bd82a",
-                "sha256:dd6e2b598849b3d7aee2295ac765a578879830fb8966f70be8cd472e6069932e",
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@@ -602,76 +629,85 @@
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@@ -696,58 +732,56 @@
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-                "sha256:b0997827b4f6a7c286c01c5f60384d218dca4ed7d9efa945c3e1aa623d5709ae",
-                "sha256:b631ef96d3222e62861443cc89d6563ba3eeb816eeb96b2629345ab795e53681",
-                "sha256:bf47c0607522fdbca6c9e817a6e81b08491de50f3766a7a0e6a5be7905961b41",
-                "sha256:f81025eddd0327c7d4cfe9b62cf33190e1e736cc6e97502b3ec425f574b3e7a8"
-            ],
-            "version": "==5.1.2"
+                "sha256:0e7f69397d53155e55d10ff68fdfb2cf630a35e6daf65cf0bdeaf04f127c09dc",
+                "sha256:2e9f0b7c5914367b0916c3c104a024bb68f269a486b9d04a2e8ac6f6597b7803",
+                "sha256:35ace9b4147848cafac3db142795ee42deebe9d0dad885ce643928e88daebdcc",
+                "sha256:38a4f0d114101c58c0f3a88aeaa44d63efd588845c5a2df5290b73db8f246d15",
+                "sha256:483eb6a33b671408c8529106df3707270bfacb2447bf8ad856a4b4f57f6e3075",
+                "sha256:4b6be5edb9f6bb73680f5bf4ee08ff25416d1400fbd4535fe0069b2994da07cd",
+                "sha256:7f38e35c00e160db592091751d385cd7b3046d6d51f578b29943225178257b31",
+                "sha256:8100c896ecb361794d8bfdb9c11fce618c7cf83d624d73d5ab38aef3bc82d43f",
+                "sha256:c0ee8eca2c582d29c3c2ec6e2c4f703d1b7f1fb10bc72317355a746057e7346c",
+                "sha256:e4c015484ff0ff197564917b4b4246ca03f411b9bd7f16e02a2f586eb48b6d04",
+                "sha256:ebc4ed52dcc93eeebeae5cf5deb2ae4347b3a81c3fa12b0b8c976544829396a4"
+            ],
+            "version": "==5.2"
         },
         "requests": {
             "hashes": [
@@ -767,54 +801,60 @@
         },
         "scipy": {
             "hashes": [
-                "sha256:03b1e0775edbe6a4c64effb05fff2ce1429b76d29d754aa5ee2d848b60033351",
-                "sha256:09d008237baabf52a5d4f5a6fcf9b3c03408f3f61a69c404472a16861a73917e",
-                "sha256:10325f0ffac2400b1ec09537b7e403419dcd25d9fee602a44e8a32119af9079e",
-                "sha256:1db9f964ed9c52dc5bd6127f0dd90ac89791daa690a5665cc01eae185912e1ba",
-                "sha256:409846be9d6bdcbd78b9e5afe2f64b2da5a923dd7c1cd0615ce589489533fdbb",
-                "sha256:4907040f62b91c2e170359c3d36c000af783f0fa1516a83d6c1517cde0af5340",
-                "sha256:6c0543f2fdd38dee631fb023c0f31c284a532d205590b393d72009c14847f5b1",
-                "sha256:826b9f5fbb7f908a13aa1efd4b7321e36992f5868d5d8311c7b40cf9b11ca0e7",
-                "sha256:a7695a378c2ce402405ea37b12c7a338a8755e081869bd6b95858893ceb617ae",
-                "sha256:a84c31e8409b420c3ca57fd30c7589378d6fdc8d155d866a7f8e6e80dec6fd06",
-                "sha256:adadeeae5500de0da2b9e8dd478520d0a9945b577b2198f2462555e68f58e7ef",
-                "sha256:b283a76a83fe463c9587a2c88003f800e08c3929dfbeba833b78260f9c209785",
-                "sha256:c19a7389ab3cd712058a8c3c9ffd8d27a57f3d84b9c91a931f542682bb3d269d",
-                "sha256:c3bb4bd2aca82fb498247deeac12265921fe231502a6bc6edea3ee7fe6c40a7a",
-                "sha256:c5ea60ece0c0c1c849025bfc541b60a6751b491b6f11dd9ef37ab5b8c9041921",
-                "sha256:db61a640ca20f237317d27bc658c1fc54c7581ff7f6502d112922dc285bdabee"
+                "sha256:00af72998a46c25bdb5824d2b729e7dabec0c765f9deb0b504f928591f5ff9d4",
+                "sha256:0902a620a381f101e184a958459b36d3ee50f5effd186db76e131cbefcbb96f7",
+                "sha256:1e3190466d669d658233e8a583b854f6386dd62d655539b77b3fa25bfb2abb70",
+                "sha256:2cce3f9847a1a51019e8c5b47620da93950e58ebc611f13e0d11f4980ca5fecb",
+                "sha256:3092857f36b690a321a662fe5496cb816a7f4eecd875e1d36793d92d3f884073",
+                "sha256:386086e2972ed2db17cebf88610aab7d7f6e2c0ca30042dc9a89cf18dcc363fa",
+                "sha256:71eb180f22c49066f25d6df16f8709f215723317cc951d99e54dc88020ea57be",
+                "sha256:770254a280d741dd3436919d47e35712fb081a6ff8bafc0f319382b954b77802",
+                "sha256:787cc50cab3020a865640aba3485e9fbd161d4d3b0d03a967df1a2881320512d",
+                "sha256:8a07760d5c7f3a92e440ad3aedcc98891e915ce857664282ae3c0220f3301eb6",
+                "sha256:8d3bc3993b8e4be7eade6dcc6fd59a412d96d3a33fa42b0fa45dc9e24495ede9",
+                "sha256:9508a7c628a165c2c835f2497837bf6ac80eb25291055f56c129df3c943cbaf8",
+                "sha256:a144811318853a23d32a07bc7fd5561ff0cac5da643d96ed94a4ffe967d89672",
+                "sha256:a1aae70d52d0b074d8121333bc807a485f9f1e6a69742010b33780df2e60cfe0",
+                "sha256:a2d6df9eb074af7f08866598e4ef068a2b310d98f87dc23bd1b90ec7bdcec802",
+                "sha256:bb517872058a1f087c4528e7429b4a44533a902644987e7b2fe35ecc223bc408",
+                "sha256:c5cac0c0387272ee0e789e94a570ac51deb01c796b37fb2aad1fb13f85e2f97d",
+                "sha256:cc971a82ea1170e677443108703a2ec9ff0f70752258d0e9f5433d00dda01f59",
+                "sha256:dba8306f6da99e37ea08c08fef6e274b5bf8567bb094d1dbe86a20e532aca088",
+                "sha256:dc60bb302f48acf6da8ca4444cfa17d52c63c5415302a9ee77b3b21618090521",
+                "sha256:dee1bbf3a6c8f73b6b218cb28eed8dd13347ea2f87d572ce19b289d6fd3fbc59"
             ],
             "index": "pypi",
-            "version": "==1.3.0"
+            "version": "==1.4.1"
         },
         "six": {
             "hashes": [
-                "sha256:3350809f0555b11f552448330d0b52d5f24c91a322ea4a15ef22629740f3761c",
-                "sha256:d16a0141ec1a18405cd4ce8b4613101da75da0e9a7aec5bdd4fa804d0e0eba73"
+                "sha256:1f1b7d42e254082a9db6279deae68afb421ceba6158efa6131de7b3003ee93fd",
+                "sha256:30f610279e8b2578cab6db20741130331735c781b56053c59c4076da27f06b66"
             ],
-            "version": "==1.12.0"
+            "version": "==1.13.0"
         },
         "snowballstemmer": {
             "hashes": [
-                "sha256:9f3b9ffe0809d174f7047e121431acf99c89a7040f0ca84f94ba53a498e6d0c9"
+                "sha256:209f257d7533fdb3cb73bdbd24f436239ca3b2fa67d56f6ff88e86be08cc5ef0",
+                "sha256:df3bac3df4c2c01363f3dd2cfa78cce2840a79b9f1c2d2de9ce8d31683992f52"
             ],
-            "version": "==1.9.0"
+            "version": "==2.0.0"
         },
         "sphinx": {
             "hashes": [
-                "sha256:22538e1bbe62b407cf5a8aabe1bb15848aa66bb79559f42f5202bbce6b757a69",
-                "sha256:f9a79e746b87921cabc3baa375199c6076d1270cee53915dbd24fdbeaaacc427"
+                "sha256:0a11e2fd31fe5c7e64b4fc53c2c022946512f021d603eb41ac6ae51d5fcbb574",
+                "sha256:138e39aa10f28d52aa5759fc6d1cba2be6a4b750010974047fa7d0e31addcf63"
             ],
             "index": "pypi",
-            "version": "==2.1.2"
+            "version": "==2.3.0"
         },
         "sphinx-autoapi": {
             "hashes": [
-                "sha256:79d11a33b436ad3c6909e1273e4c36de0c54c5da98d6aa3b4a3665204cfbcb28",
-                "sha256:a450cb8b5c0bdaf9c95b983f1e151d598e7d9a062db5085a8fe7b55eec8700ec"
+                "sha256:623646ed1be7127486cab5f4e3ffc17a9327c2d2f3fce18effc39d73975a2973",
+                "sha256:b6b5f008edc174768a4d1fa87bc8ba1287744c9a9ff82e49064783da7a2ad03e"
             ],
             "index": "pypi",
-            "version": "==1.1.0"
+            "version": "==1.2.1"
         },
         "sphinxcontrib-applehelp": {
             "hashes": [
@@ -830,20 +870,6 @@
             ],
             "version": "==1.0.1"
         },
-        "sphinxcontrib-dotnetdomain": {
-            "hashes": [
-                "sha256:985cfdba4bf67bd5af736bab76e9f206ae987c64198e6d42c7043cde11dfc374",
-                "sha256:c41bf7a9627f0b804be1992c4b62cbf4c757d26ff7d2541eb13f68981b180073"
-            ],
-            "version": "==0.4"
-        },
-        "sphinxcontrib-golangdomain": {
-            "hashes": [
-                "sha256:7bcd4bb6443d5f9b06e0e9b48dadb2e42967dd8c7d67ad03e501ea4575c55b26",
-                "sha256:dd49dc19140cbefad5af4f0157174eecfe075bcce4ad7a8ef725e8b81ab0744b"
-            ],
-            "version": "==0.2.0.dev0"
-        },
         "sphinxcontrib-htmlhelp": {
             "hashes": [
                 "sha256:4670f99f8951bd78cd4ad2ab962f798f5618b17675c35c5ac3b2132a14ea8422",
@@ -874,23 +900,28 @@
         },
         "typed-ast": {
             "hashes": [
+                "sha256:1170afa46a3799e18b4c977777ce137bb53c7485379d9706af8a59f2ea1aa161",
                 "sha256:18511a0b3e7922276346bcb47e2ef9f38fb90fd31cb9223eed42c85d1312344e",
                 "sha256:262c247a82d005e43b5b7f69aff746370538e176131c32dda9cb0f324d27141e",
                 "sha256:2b907eb046d049bcd9892e3076c7a6456c93a25bebfe554e931620c90e6a25b0",
                 "sha256:354c16e5babd09f5cb0ee000d54cfa38401d8b8891eefa878ac772f827181a3c",
+                "sha256:48e5b1e71f25cfdef98b013263a88d7145879fbb2d5185f2a0c79fa7ebbeae47",
                 "sha256:4e0b70c6fc4d010f8107726af5fd37921b666f5b31d9331f0bd24ad9a088e631",
                 "sha256:630968c5cdee51a11c05a30453f8cd65e0cc1d2ad0d9192819df9978984529f4",
                 "sha256:66480f95b8167c9c5c5c87f32cf437d585937970f3fc24386f313a4c97b44e34",
                 "sha256:71211d26ffd12d63a83e079ff258ac9d56a1376a25bc80b1cdcdf601b855b90b",
+                "sha256:7954560051331d003b4e2b3eb822d9dd2e376fa4f6d98fee32f452f52dd6ebb2",
+                "sha256:838997f4310012cf2e1ad3803bce2f3402e9ffb71ded61b5ee22617b3a7f6b6e",
                 "sha256:95bd11af7eafc16e829af2d3df510cecfd4387f6453355188342c3e79a2ec87a",
                 "sha256:bc6c7d3fa1325a0c6613512a093bc2a2a15aeec350451cbdf9e1d4bffe3e3233",
                 "sha256:cc34a6f5b426748a507dd5d1de4c1978f2eb5626d51326e43280941206c209e1",
                 "sha256:d755f03c1e4a51e9b24d899561fec4ccaf51f210d52abdf8c07ee2849b212a36",
                 "sha256:d7c45933b1bdfaf9f36c579671fec15d25b06c8398f113dab64c18ed1adda01d",
                 "sha256:d896919306dd0aa22d0132f62a1b78d11aaf4c9fc5b3410d3c666b818191630a",
+                "sha256:fdc1c9bbf79510b76408840e009ed65958feba92a88833cdceecff93ae8fff66",
                 "sha256:ffde2fbfad571af120fcbfbbc61c72469e72f550d676c3342492a9dfdefb8f12"
             ],
-            "markers": "implementation_name == 'cpython'",
+            "markers": "implementation_name == 'cpython' and python_version < '3.8'",
             "version": "==1.4.0"
         },
         "unidecode": {
@@ -902,10 +933,10 @@
         },
         "urllib3": {
             "hashes": [
-                "sha256:b246607a25ac80bedac05c6f282e3cdaf3afb65420fd024ac94435cabe6e18d1",
-                "sha256:dbe59173209418ae49d485b87d1681aefa36252ee85884c31346debd19463232"
+                "sha256:a8a318824cc77d1fd4b2bec2ded92646630d7fe8619497b142c84a9e6f5a7293",
+                "sha256:f3c5fd51747d450d4dcf6f923c81f78f811aab8205fda64b0aba34a4e48b0745"
             ],
-            "version": "==1.25.3"
+            "version": "==1.25.7"
         },
         "wcwidth": {
             "hashes": [
@@ -922,10 +953,10 @@
         },
         "zipp": {
             "hashes": [
-                "sha256:4970c3758f4e89a7857a973b1e2a5d75bcdc47794442f2e2dd4fe8e0466e809a",
-                "sha256:8a5712cfd3bb4248015eb3b0b3c54a5f6ee3f2425963ef2a0125b8bc40aafaec"
+                "sha256:3718b1cbcd963c7d4c5511a8240812904164b7f381b647143a89d3b98f9bcd8e",
+                "sha256:f06903e9f1f43b12d371004b4ac7b06ab39a44adc747266928ae6debfa7b3335"
             ],
-            "version": "==0.5.2"
+            "version": "==0.6.0"
         }
     }
 }
diff --git a/README.rst b/README.rst
index 95bcccd0..68ab57d3 100644
--- a/README.rst
+++ b/README.rst
@@ -72,26 +72,22 @@ Overall Architecture
 
 ::
 
-      ============       +-----------------+       ===================
-    || model file || --> | frontend Parser | --> || uTensorGraph (IR) ||
-      ============       +-----------------+       ===================
-                                                               |
-                     +-------------------------------+         |
-                     |       graph transformer       |         |
-                     | (legalization & optimization) | <------/
-                     +-------------------------------+
-                                    |
-                                    v
-                         ===========================
-                       ||       uTensorGraph        ||
-                       || (legalized and optimized) ||
-                         ===========================
-                                       |
-    +--------------------------+       |
-    | backend (code generator) | <----/
+      ============       +-----------------+       ============================
+    || model file || --> | frontend Parser | --> || uTensorGraph (IR, generic) ||
+      ============       +-----------------+       ============================
+                                                                |
+                                                                v
+                                                     +---------------------+
+                        =======================      |  graph transformer  |
+                      ||     uTensorGraph     || <-- |    (optimization)   |
+                      || (generic, optimized) ||     +---------------------+
+                        =======================                                    
+                                     |
+    +--------------------------+     |
+    | backend (code generator) | <--/
     +--------------------------+
          |
-         `---> (target files, ex: model.cpp, model.hpp, weights.idx)
+         `---> (target files, ex: model.cpp, model.hpp, weights.idx, ...etc)
 
 Basic Usage
 ===========
@@ -114,7 +110,8 @@ Convert Model File to C/C++ Code
 .. code-block:: console
 
   $ utensor-cli convert <model.pb> \
-    --output-nodes=<node_name>[,<node_name>,...]
+    --output-nodes=<node name>[,<node name>,...] \
+    [--config=config.toml]
 
 Convert given pb file into cpp/hpp files.
 
@@ -123,6 +120,8 @@ nodes you want to output, seperated by comma for multiple values.
 
 In graph theory terminology, they are ``leaf`` nodes of your graph.
 
+Use ``--config`` to pass a configuration file to the cli, you can use ``generate-config`` command to generate one (see below).
+
 example
 ~~~~~~~
 
@@ -132,8 +131,34 @@ example
 
 Run ``utensor-cli convert --help`` for detailed information.
 
-:mod:`utensor_cgen` as Library
-==============================
+Configuration
+-------------
+
+``utensor-cli`` use ``toml`` as configuration format.
+
+You can generate configuration file of given target as following:
+
+.. code-block:: console
+
+  $ utensor-cli generate-config --target <target name> [-o filename.toml]
+
+This command will generate a ``toml`` file listing all configurable values with its defaults.
+
+You can modify the value and pass the file to cli with ``--config`` flag.
+
+example
+~~~~~~~
+
+.. code-block:: console
+
+  # generate config file
+  $ utensor-cli generate-config --target utensor -o myconfig.toml
+
+  # after editting myconfig.toml
+  $ utensor-cli convert mymodel.pb --config=myconfig.toml --output-nodes=output,...
+
+Use :mod:`utensor_cgen` as Library
+==================================
 
 .. subgraph-match-begine
 
@@ -223,8 +248,8 @@ TensorFlow_
 
 1. Freeze your `tensorflow.Graph`
 
-  - please refer to the `official doc <https://www.tensorflow.org/guide/extend/model_files>`_
-    and read the `Freezing <https://www.tensorflow.org/guide/extend/model_files#freezing>`_ section
+  - please refer to this `issue track <https://github.com/tensorflow/tensorflow/issues/27614>`_ for detail
+  - especially this `comment <https://github.com/tensorflow/tensorflow/issues/27614#issuecomment-571889676>`_ by Robin2091
 
 2. Follow instructions in :ref:`install` section to install :mod:`utensor_cgen`
 
diff --git a/example_config.toml b/example_config.toml
new file mode 100644
index 00000000..6cc4500a
--- /dev/null
+++ b/example_config.toml
@@ -0,0 +1,15 @@
+# https://github.com/toml-lang/toml
+# <target_name>.<component>.<part>
+[utensor.backend]
+legacy-api = true
+
+[utensor.backend.legacy_code_generator]
+src_fname = "None"
+params_dir = "data"
+embed_params_dir = "/fs/data"
+model_dir = "models"
+transform_methods = [ "dropout(name_pattern=r\"(dropout[_\\w\\d]*)/.*\")", "linear_reorder", "quantize", "conv_pool", "inline", "biasAdd", "remove_id_op", "fake_gather_v2", "refcnt",]
+save_graph = false
+debug_cmt = false
+
+[utensor.backend.graph_lower]
diff --git a/plugins/dummy_backend/__init__.py b/plugins/dummy_backend/__init__.py
new file mode 100644
index 00000000..2e422f1e
--- /dev/null
+++ b/plugins/dummy_backend/__init__.py
@@ -0,0 +1,34 @@
+from textwrap import wrap
+
+from utensor_cgen.backend.base import Backend
+from utensor_cgen.backend import BackendManager
+from utensor_cgen.utils import class_property
+
+@BackendManager.register
+class DummyBackend(Backend):
+    TARGET = 'dummy-backend'
+
+    def __init__(self, config):
+        if not config:
+            config = self.default_config
+        self.output_file = config[self.TARGET][self.COMPONENT]['output-file']
+
+    def apply(self, ugraph):
+        with open(self.output_file, 'w') as fid:
+            fid.write('#include <stdio.h>\n\n')
+            fid.write('int main(int argc, char* argv[]) {\n')
+            fid.write('    printf("graph name: {}\\n");\n'.format(ugraph.name))
+            fid.write('    printf("ops in topological sorted order:\\n");\n')
+            for op_name in ugraph.topo_order:
+                fid.write('    printf("    {}\\n");\n'.format(op_name))
+            fid.write('    return 0;\n}')
+
+    @class_property
+    def default_config(cls):
+        return {
+            cls.TARGET: {
+                    cls.COMPONENT: {
+                    'output-file': 'list_op.c'
+                }
+            }
+        }
diff --git a/setup.py b/setup.py
index 63849a6b..3e08546e 100644
--- a/setup.py
+++ b/setup.py
@@ -3,27 +3,48 @@
 import os
 
 from setuptools import find_packages, setup
+from setuptools.command.develop import develop as _develop
+from setuptools.command.install import install as _install
 
 root_dir = os.path.abspath(os.path.dirname(__file__))
 with open(os.path.join(root_dir, "LICENSE")) as rf:
     license = rf.read()
 
+
+class _CompileFlatbuffMixin(object):
+
+    def run(self):
+        super(_CompileFlatbuffMixin, self).run()
+        self._build_flatbuffer()
+
+    def _build_flatbuffer(self):
+        install_dir = self.install_platlib
+        if install_dir is None:
+            install_dir = os.path.abspath('utensor')
+
+
+class _Install(_CompileFlatbuffMixin, _install): pass
+
+
+class _Develop(_CompileFlatbuffMixin, _develop): pass
+
+
 setup(
     name='utensor_cgen',
     version_config={
         "starting_version": "0.0.0",
-        "version_format": "{tag}.dev{sha:.7s}"
+        "version_format": "{tag}.{sha:.7s}.dev"
     },
     setup_requires=['better-setuptools-git-version'],
+    cmdclass={'install': _Install, 'develop': _Develop},
     description="C code generation program for uTensor",
     long_description="please go to [doc](https://utensor-cgen.readthedocs.io/en/latest/) page for more information",
-    url="https://github.com/dboyliao/utensor_cgen",
+    url="https://github.com/uTensor/utensor_cgen",
     author="Dboy Liao",
     author_email="qmalliao@gmail.com",
     license=license,
     packages=find_packages(),
-    include_package_data=True,
-    package_data={"utensor_cgen": ["backend/snippets/templates/*"]},
+    package_data={'utensor_cgen.backend.utensor.snippets': ["templates/*/*/*"]},
     entry_points={
         "console_scripts": [
             "utensor-cli=utensor_cgen.cli:cli"
@@ -38,7 +59,8 @@
         'torchvision',
         'onnx-tf==1.2.1',
         'graphviz',
-        'flatbuffers'
+        'flatbuffers',
+        'toml',
     ],
     extras_require={
         'dev': ['pytest']
diff --git a/tests/test_backend/__init__.py b/tests/test_backend/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/tests/test_backend/conftest.py b/tests/test_backend/conftest.py
new file mode 100644
index 00000000..51cfa229
--- /dev/null
+++ b/tests/test_backend/conftest.py
@@ -0,0 +1,14 @@
+import os
+from pytest import fixture
+
+@fixture(scope='session', name='mlp_ugraph')
+def mlp_ugraph():
+    from utensor_cgen.frontend import FrontendSelector
+    model_file = os.path.join(
+        os.path.abspath(
+            os.path.join(
+                os.path.dirname(__file__), '..')
+            ),
+            'deep_mlp/simple_mnist.pb'
+    )
+    return FrontendSelector.parse(model_file, output_nodes=['y_pred'])
diff --git a/tests/test_backend/test_utensor.py b/tests/test_backend/test_utensor.py
new file mode 100644
index 00000000..aa41b5d8
--- /dev/null
+++ b/tests/test_backend/test_utensor.py
@@ -0,0 +1,19 @@
+import os
+
+def test_legacy_utensor(mlp_ugraph):
+    from utensor_cgen.backend.utensor import uTensorBackend
+
+    this_dir = os.path.dirname(__file__)
+
+    uTensorBackend(config={
+        'utensor': {
+            'backend': {
+                'legacy-api': True,
+                'code_generator': {
+                    'model_dir': os.path.join(this_dir, 'models'),
+                    'params_dir': os.path.join(this_dir, 'data'),
+                },
+                'graph_lower': {}
+            },
+        }
+    }).apply(mlp_ugraph)
diff --git a/tests/test_ir/test_uTensorGraph/test_graph.py b/tests/test_ir/test_uTensorGraph/test_graph.py
index ecb6a2c0..6a60e595 100644
--- a/tests/test_ir/test_uTensorGraph/test_graph.py
+++ b/tests/test_ir/test_uTensorGraph/test_graph.py
@@ -36,7 +36,7 @@ def test_op_info():
                             output_tensors=[],
                             n_outputs=0,
                             op_type='no_op',
-                            backend='tensorflow',
+                            lib_name='tensorflow',
                             op_attr={
                                 '_utensor_to_skip': [1, 2, 3],
                                 '_utensor_skip_this_too': None,
diff --git a/tests/test_transformer/test_convpool/test_vgg.py b/tests/test_transformer/test_convpool/test_vgg.py
index 8660ab2e..f9af19c1 100644
--- a/tests/test_transformer/test_convpool/test_vgg.py
+++ b/tests/test_transformer/test_convpool/test_vgg.py
@@ -4,9 +4,9 @@
 def factory():
     def test(vgg_ugraph):
         trans = TransformerPipeline([
-            ('linear_reorder', {}),
-            ('quantize', {}),
-            ('conv_pool', {})
+            'linear_reorder',
+            'quantize',
+            'conv_pool',
         ])
         new_ugraph = trans.transform(vgg_ugraph)
         num_conv = len(vgg_ugraph.get_ops_by_type('Conv2D'))
diff --git a/tests/test_transformer/test_linear_reorder/conftest.py b/tests/test_transformer/test_linear_reorder/conftest.py
index 94944398..e69dd354 100644
--- a/tests/test_transformer/test_linear_reorder/conftest.py
+++ b/tests/test_transformer/test_linear_reorder/conftest.py
@@ -11,9 +11,9 @@ def subject_ugraph_1():
         input_1 = tf.placeholder(dtype=tf.float32, shape=[None, 512, 512, 10], name='input_1')
         relu_1 = tf.nn.relu(input_1, name='relu_1')
         max_pool_1 = tf.nn.max_pool(relu_1, ksize=[1, 3, 3, 1], strides=[1, 2, 2, 1], padding='VALID', name='pool_1')
-        input_2 = tf.placeholder(dtype=tf.float32, shape=[None, 512, 512, 3], name='input_2')
-        relu_2 = tf.nn.relu(input_1, name='relu_2')
-        max_pool_2 = tf.nn.max_pool(relu_1, ksize=[1, 3, 3, 1], strides=[1, 2, 2, 1], padding='VALID', name='pool_2')
+        input_2 = tf.placeholder(dtype=tf.float32, shape=[None, 512, 512, 10], name='input_2')
+        relu_2 = tf.nn.relu(input_2, name='relu_2')
+        max_pool_2 = tf.nn.max_pool(relu_2, ksize=[1, 3, 3, 1], strides=[1, 2, 2, 1], padding='VALID', name='pool_2')
         output = tf.add(max_pool_1, max_pool_2, name='output')
-    subj_ugraph = GraphDefParser.parse(graph.as_graph_def(), output_nodes=['output'])
+    subj_ugraph = GraphDefParser.parse(graph.as_graph_def(), output_nodes=[output.op.name])
     return subj_ugraph
diff --git a/tests/test_transformer/test_pipeline/conftest.py b/tests/test_transformer/test_pipeline/conftest.py
index 9e0c2d41..a71cf887 100644
--- a/tests/test_transformer/test_pipeline/conftest.py
+++ b/tests/test_transformer/test_pipeline/conftest.py
@@ -8,9 +8,11 @@
 
 @pytest.fixture(scope='function', name='methods')
 def pipeline_methods():
-    all_methods = [(BatchNormTransformer.METHOD_NAME, {}),
-                   (DropoutTransformer.METHOD_NAME, {}),
-                   (QuantizeTransformer.METHOD_NAME, {}),
-                   (RefCntOptimizer.METHOD_NAME, {})]
+    all_methods = [
+        BatchNormTransformer.METHOD_NAME,
+        DropoutTransformer.METHOD_NAME,
+        QuantizeTransformer.METHOD_NAME,
+        RefCntOptimizer.METHOD_NAME,
+    ]
     shuffle(all_methods)
     return all_methods
diff --git a/tests/test_transformer/test_pipeline/test_pipeline_transformer.py b/tests/test_transformer/test_pipeline/test_pipeline_transformer.py
index 1e1213f7..b2e64823 100644
--- a/tests/test_transformer/test_pipeline/test_pipeline_transformer.py
+++ b/tests/test_transformer/test_pipeline/test_pipeline_transformer.py
@@ -5,17 +5,17 @@
 def test_pipeline_1(methods):
     pipeline = TransformerPipeline(methods)
     assert len(pipeline.pipeline) == len(methods)
-    for transformer, (method_name, _) in zip(pipeline.pipeline, methods):
+    for transformer, method_name in zip(pipeline.pipeline, methods):
         assert isinstance(transformer, pipeline.TRANSFORMER_MAP[method_name])
 
 def test_pipeline_2(methods):
     pipeline = TransformerPipeline(methods)
     assert len(pipeline.pipeline) == len(methods)
-    for transformer, (method_name, _) in zip(pipeline.pipeline, methods):
+    for transformer, method_name in zip(pipeline.pipeline, methods):
         assert isinstance(transformer, pipeline.TRANSFORMER_MAP[method_name])
 
 def test_pipeline_3(methods):
     pipeline = TransformerPipeline(methods)
     assert len(pipeline.pipeline) == len(methods)
-    for transformer, (method_name, _) in zip(pipeline.pipeline, methods):
+    for transformer, method_name in zip(pipeline.pipeline, methods):
         assert isinstance(transformer, pipeline.TRANSFORMER_MAP[method_name])
diff --git a/utensor_cgen/__init__.py b/utensor_cgen/__init__.py
index e69de29b..c8e03414 100644
--- a/utensor_cgen/__init__.py
+++ b/utensor_cgen/__init__.py
@@ -0,0 +1,12 @@
+import sys
+
+import pkg_resources
+
+from utensor_cgen._extensions import _ExtensionsLoader
+
+__version__ = (
+  pkg_resources
+  .get_distribution('utensor_cgen')
+  .version
+)
+sys.modules['utensor_cgen.extensions'] = _ExtensionsLoader()
diff --git a/utensor_cgen/_extensions.py b/utensor_cgen/_extensions.py
new file mode 100644
index 00000000..5a748c3b
--- /dev/null
+++ b/utensor_cgen/_extensions.py
@@ -0,0 +1,26 @@
+import sys
+import re
+import importlib
+from types import ModuleType
+
+class _ExtensionsLoader(ModuleType):
+  _ext_cache = {}
+  _dunder_pattern = re.compile(r'__[A-Za-z0-9_]+__')
+
+  def __init__(self):
+    super(_ExtensionsLoader, self).__init__('utensor_cgen.extensions', {})
+    
+  def __getattr__(self, ext_name):
+    if self._dunder_pattern.match(ext_name):
+      _mod = sys.modules['utensor_cgen._extensions']
+      return getattr(_mod, ext_name)
+    if ext_name not in self._ext_cache:
+      ext_mod = importlib.import_module(
+          'utensor_{}'.format(ext_name)
+      )
+      self._ext_cache[ext_name] = ext_mod
+      sys.modules['utensor_cgen.extensions.{}'.format(ext_name)] = ext_mod
+    return self._ext_cache[ext_name]
+    
+  def __dir__(self):
+    return self._ext_cache.keys()
diff --git a/utensor_cgen/backend/__init__.py b/utensor_cgen/backend/__init__.py
index a6429329..7387b92d 100644
--- a/utensor_cgen/backend/__init__.py
+++ b/utensor_cgen/backend/__init__.py
@@ -1,2 +1 @@
-from .code_generator import CodeGenerator
-from .operators import OperatorFactory
\ No newline at end of file
+from .api import BackendManager
diff --git a/utensor_cgen/backend/api.py b/utensor_cgen/backend/api.py
new file mode 100644
index 00000000..769863fa
--- /dev/null
+++ b/utensor_cgen/backend/api.py
@@ -0,0 +1,28 @@
+from utensor_cgen.utils import class_property
+
+from .base import Backend
+from .utensor import uTensorBackend
+
+
+class BackendManager(object):
+  BACKENDS = {}
+
+  @classmethod
+  def get_backend(cls, name):
+    if name not in cls.BACKENDS:
+      raise ValueError('unknown backend name: %s' % name)
+    return cls.BACKENDS[name]
+
+  @classmethod
+  def register(cls, backend_cls):
+    if not issubclass(backend_cls, Backend):
+      raise TypeError(
+        'can only register subclass of %s: get %s' % (Backend, backend_cls)
+      )
+    cls.BACKENDS[backend_cls.TARGET] = backend_cls
+
+  @class_property
+  def backends(cls):
+    return list(cls.BACKENDS.keys())
+
+BackendManager.register(uTensorBackend)
diff --git a/utensor_cgen/backend/base.py b/utensor_cgen/backend/base.py
new file mode 100644
index 00000000..ed74618a
--- /dev/null
+++ b/utensor_cgen/backend/base.py
@@ -0,0 +1,87 @@
+from utensor_cgen.utils import (
+  MUST_OVERWRITEN, class_property,
+  parse_toml, Configuration,
+)
+
+
+class _BackendBase(object):
+
+  COMPONENT = 'backend'
+
+  def __new__(cls, config, *args, **kwargs):
+    self = object.__new__(cls)
+    for name in dir(self):
+      if name.startswith('_validate'):
+        validator = getattr(self, name)
+        validator(config, *args, **kwargs)
+    if isinstance(config, dict):
+      config = Configuration(cls.default_config, config)
+    self._config = config
+    return self
+
+  def apply(self, ugraph):
+    raise NotImplementedError('all backend object must overwrite apply method')
+
+  @class_property
+  def default_config(cls):
+    return NotImplementedError('All backends should overwrite default config')
+
+  def __call__(self, *args, **kwargs):
+    return self.apply(*args, **kwargs)
+
+  @property
+  def config(self):
+    return self._config
+
+  def _validate_config(self, config):
+    assert isinstance(config, (dict, Configuration)), \
+      'expecting {}, get {}'.format(dict, type(config))
+
+
+class Backend(_BackendBase):
+
+  TARGET = MUST_OVERWRITEN
+
+  @classmethod
+  def _validate_target(cls, config, *args, **kwargs):
+    if cls.TARGET is MUST_OVERWRITEN:
+      raise ValueError(
+        'Every Backend must overwrite TARGET attribute: {}'.format(cls)
+      )
+
+  @classmethod
+  def from_file(cls, file_or_path, *args, **kwargs):
+    config = parse_toml(file_or_path)[cls.TARGET][cls.COMPONENT]
+    return cls(config, *args, **kwargs)
+
+  @classmethod
+  def from_config(cls, config, *args, **kwargs):
+    return cls(config, *args, **kwargs)
+
+class BackendPart(Backend):
+
+  PART = MUST_OVERWRITEN
+
+  @classmethod
+  def _validate_part(cls, config, *args, **kwargs):
+    if cls.PART is MUST_OVERWRITEN:
+      raise ValueError(
+        'Every BackendPart must overwrite PART attribute: {}'.format(cls)
+      )
+
+  @classmethod
+  def from_config(cls, config, *args, **kwargs):
+    default_config = cls.default_config
+    if cls.TARGET in config:
+      config = config[cls.TARGET]
+    if cls.COMPONENT in config:
+      config = config[cls.COMPONENT]
+    if cls.PART in config:
+      config = config[cls.PART]
+    default_config.update(config)
+    return cls(default_config, *args, **kwargs)
+
+  @classmethod
+  def from_file(cls, file_or_path, *args, **kwargs):
+    config = parse_toml(file_or_path)[cls.TARGET][cls.COMPONENT][cls.PART]
+    return cls(config, *args, **kwargs)
diff --git a/utensor_cgen/backend/snippets/__init__.py b/utensor_cgen/backend/snippets/__init__.py
deleted file mode 100644
index 0ebed11a..00000000
--- a/utensor_cgen/backend/snippets/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from ._snippets import *
diff --git a/utensor_cgen/backend/snippets/_types.py b/utensor_cgen/backend/snippets/_types.py
deleted file mode 100644
index 50610e26..00000000
--- a/utensor_cgen/backend/snippets/_types.py
+++ /dev/null
@@ -1,27 +0,0 @@
-# -*- coding:utf8 -*-
-from collections import namedtuple
-
-import numpy as np
-import tensorflow as tf
-
-_TYPE_MAP_VALUE = namedtuple("_TYPE_MAP_VALUE", ["importer_type_str", "tensor_type_str"])
-
-NP_TYPES_MAP = {
-  np.dtype(tf.float32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="float",
-                                                       tensor_type_str="float"),
-  np.dtype(tf.qint8.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="byte", 
-                                                     tensor_type_str="uint8_t"),
-  np.dtype(tf.int32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
-                                                     tensor_type_str="int"),
-  np.dtype(tf.int64.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
-                                                     tensor_type_str="int"),
-  np.dtype(tf.quint8.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="ubyte",
-                                                      tensor_type_str="uint8_t"),
-  np.dtype(tf.qint32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
-                                                      tensor_type_str="int"),
-  np.dtype('uint16'): _TYPE_MAP_VALUE(importer_type_str="ushort",
-                                                      tensor_type_str="uint16_t"),
-  np.dtype('int8'): _TYPE_MAP_VALUE(importer_type_str="int8",
-                                                      tensor_type_str="q7_t"),
-}
-del _TYPE_MAP_VALUE
diff --git a/utensor_cgen/backend/utensor/__init__.py b/utensor_cgen/backend/utensor/__init__.py
new file mode 100644
index 00000000..ed85033c
--- /dev/null
+++ b/utensor_cgen/backend/utensor/__init__.py
@@ -0,0 +1 @@
+from ._backend_impl import uTensorBackend
diff --git a/utensor_cgen/backend/utensor/_backend_impl.py b/utensor_cgen/backend/utensor/_backend_impl.py
new file mode 100644
index 00000000..cc5db5b7
--- /dev/null
+++ b/utensor_cgen/backend/utensor/_backend_impl.py
@@ -0,0 +1,62 @@
+from utensor_cgen.backend.base import Backend
+from utensor_cgen.utils import (
+  class_property, parse_toml,
+  LazyLoader, LazyAttrib,
+  Configuration,
+)
+
+code_generator = LazyLoader(submod_name='backend.utensor.code_generator')
+_graph_lower = LazyLoader(submod_name='backend.utensor._graph_lower')
+uTensorLegacyCodeGenerator = LazyAttrib(code_generator, 'uTensorLegacyCodeGenerator')
+uTensorRearchCodeGenerator = LazyAttrib(code_generator, 'uTensorRearchCodeGenerator')
+uTensorLegacyGraphLower = LazyAttrib(_graph_lower, 'uTensorLegacyGraphLower')
+uTensorRearchGraphLower = LazyAttrib(_graph_lower, 'uTensorRearchGraphLower')
+
+del code_generator, _graph_lower
+
+class uTensorBackend(Backend):
+
+  TARGET = 'utensor'
+
+  def __init__(self, config, code_generator=None, graph_lower=None):
+    default_config = self.default_config[self.TARGET][self.COMPONENT]
+    config = Configuration(default_config, config.get(
+      self.TARGET,
+      {self.COMPONENT: {}}
+    ).get(
+      self.COMPONENT, {}
+      )
+    )
+    if config['legacy-api']:
+      code_generator = code_generator or uTensorLegacyCodeGenerator(config=config[uTensorLegacyCodeGenerator.PART])
+      graph_lower = graph_lower or uTensorLegacyGraphLower(config=config[uTensorLegacyGraphLower.PART])
+    else:
+      code_generator = code_generator or uTensorRearchCodeGenerator(config=config[uTensorRearchCodeGenerator.PART])
+      graph_lower = graph_lower or uTensorRearchGraphLower(config=config[uTensorRearchGraphLower.PART])
+    self._graph_lower = graph_lower
+    self._code_generator = code_generator
+  
+  @class_property
+  def default_config(cls):
+    config = {}
+    config[cls.TARGET] = {}
+    config[cls.TARGET][cls.COMPONENT] = {}
+    config[cls.TARGET][cls.COMPONENT]['legacy-api'] = True
+    config[cls.TARGET][cls.COMPONENT][uTensorLegacyCodeGenerator.PART] = uTensorLegacyCodeGenerator.default_config
+    config[cls.TARGET][cls.COMPONENT][uTensorRearchCodeGenerator.PART] = uTensorRearchCodeGenerator.default_config
+    config[cls.TARGET][cls.COMPONENT][uTensorLegacyGraphLower.PART] = uTensorLegacyGraphLower.default_config
+    config[cls.TARGET][cls.COMPONENT][uTensorRearchGraphLower.PART] = uTensorRearchGraphLower.default_config
+    return config
+
+  def apply(self, ugraph):
+    lower_ugraph = self._graph_lower.apply(ugraph)
+    self._code_generator.apply(lower_ugraph)
+    return lower_ugraph
+
+  def __call__(self, ugraph):
+    return self.apply(ugraph)
+
+  @classmethod
+  def from_file(cls, path_or_file):
+    config = parse_toml(path_or_file)
+    return cls(config=config)
diff --git a/utensor_cgen/backend/utensor/_graph_lower.py b/utensor_cgen/backend/utensor/_graph_lower.py
new file mode 100644
index 00000000..8ba62a17
--- /dev/null
+++ b/utensor_cgen/backend/utensor/_graph_lower.py
@@ -0,0 +1,61 @@
+from copy import deepcopy
+
+from utensor_cgen.backend.base import BackendPart
+from utensor_cgen.utils import class_property
+
+
+class uTensorLegacyGraphLower(BackendPart):
+
+  TARGET = 'utensor'
+  PART = 'legacy_graph_lower'
+
+  def apply(self, ugraph):
+    handler = getattr(self, 'handle_{}'.format(ugraph.lib_name))
+    if handler is None:
+      raise RuntimeError(
+        'can not lower ugraph from {} to utensor'.format(ugraph.lib_name)
+      )
+    return handler(ugraph)
+
+  def handle_tensorflow(self, ugraph):
+    return ugraph
+
+  @class_property
+  def default_config(cls):
+    return {}
+
+
+class uTensorRearchGraphLower(BackendPart):
+  TARGET = 'utensor'
+  PART = 'rearch_graph_lower'
+
+  class OptypRenameManager(object):
+    NAME_MAP = {
+      'Add': 'AddOperator',
+      'Conv2D': 'ConvOperator',
+      'MatMul': 'MatrixMultOperator'
+    }
+
+    @classmethod
+    def get_new_optype(cls, op_type):
+      return cls.NAME_MAP.get(op_type, op_type)
+
+  def apply(self, ugraph):
+    handler = getattr(self, 'handle_{}'.format(ugraph.lib_name))
+    if handler is None:
+      raise RuntimeError(
+        'can not lower ugraph from {} to utensor'.format(ugraph.lib_name)
+      )
+    return handler(ugraph)
+
+  def handle_tensorflow(self, ugraph):
+    new_ugraph = deepcopy(ugraph)
+    for op_info in new_ugraph.ops_info.values():
+      op_info.op_type = self.OptypRenameManager.get_new_optype(op_info.op_type)
+    return new_ugraph
+  
+  @class_property
+  def default_config(cls):
+    return {}
+  
+
diff --git a/utensor_cgen/backend/utensor/code_generator/__init__.py b/utensor_cgen/backend/utensor/code_generator/__init__.py
new file mode 100644
index 00000000..05e70bf4
--- /dev/null
+++ b/utensor_cgen/backend/utensor/code_generator/__init__.py
@@ -0,0 +1,2 @@
+from .legacy import uTensorLegacyCodeGenerator
+from .rearch import uTensorRearchCodeGenerator
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/code_generator/legacy/__init__.py b/utensor_cgen/backend/utensor/code_generator/legacy/__init__.py
new file mode 100644
index 00000000..a6f33919
--- /dev/null
+++ b/utensor_cgen/backend/utensor/code_generator/legacy/__init__.py
@@ -0,0 +1 @@
+from ._code_generator import uTensorLegacyCodeGenerator
\ No newline at end of file
diff --git a/utensor_cgen/backend/code_generator.py b/utensor_cgen/backend/utensor/code_generator/legacy/_code_generator.py
similarity index 53%
rename from utensor_cgen/backend/code_generator.py
rename to utensor_cgen/backend/utensor/code_generator/legacy/_code_generator.py
index 5ba2c674..da269a0f 100644
--- a/utensor_cgen/backend/code_generator.py
+++ b/utensor_cgen/backend/utensor/code_generator/legacy/_code_generator.py
@@ -6,90 +6,81 @@
 
 import numpy as np
 
-import tensorflow as tf
-from tensorflow.core.framework.graph_pb2 import GraphDef
-from tensorflow.tools.graph_transforms import TransformGraph
+from utensor_cgen.backend.base import BackendPart
 from utensor_cgen.frontend import FrontendSelector
 from utensor_cgen.ir import uTensorGraph
 from utensor_cgen.transformer.optimizer import RefCntOptimizer
 from utensor_cgen.transformer.pipeline import TransformerPipeline
-from utensor_cgen.utils import NamescopedKWArgsParser
+from utensor_cgen.utils import (NamescopedKWArgsParser, class_property,
+                                parse_toml, LazyLoader, Configuration)
+from utensor_cgen.backend.utensor.snippets.legacy import (
+  CommentSnippet, ContextGlobalArrayContainer,
+  ContextHeaderSnippet, ContextSnippetsContainer,
+  CreateTensorBinarySnippet, CreateTensorIdxSnippet
+)
+from utensor_cgen.backend.utensor.snippets.composer import Composer
 
-from .operators import OperatorFactory
-from .snippets import (CommentSnippet, ContextGlobalArrayContainer,
-                       ContextHeaderSnippet, ContextSnippetsContainer,
-                       CreateTensorBinarySnippet, CreateTensorIdxSnippet)
-from .snippets.composer import Composer
+from ._operators import OperatorFactory
 
-__all__ = ["CodeGenerator"]
+__all__ = ["uTensorLegacyCodeGenerator"]
 _logger = logging.getLogger('utensor-cli')
+tf = LazyLoader('tensorflow')
 
-class CodeGenerator(object):
-  def __init__(self, model_file,
-               idx_dir,
-               embed_data_dir,
-               trans_methods, # [(trans_name, kwargs),...]
-               output_nodes,
-               save_graph=False,
-               debug_cmt=False):
-    self.model_file = model_file
-    if not os.path.exists(idx_dir):
-      os.makedirs(idx_dir)
-    self.idx_dir = idx_dir
-    self.embed_data_dir = embed_data_dir.rstrip("/")
-    self.trans_methods = trans_methods
-    self.output_nodes = output_nodes
-    self.save_graph = save_graph
-    self.debug_cmt = debug_cmt
-
-  def generate(self, src_fname):
-    _, ext = os.path.splitext(self.model_file)
-    parser_cls = FrontendSelector.select_parser(ext)
-    ugraph = parser_cls.parse(self.model_file, self.output_nodes)
-    self._generate(src_fname, ugraph)
-
-  def _generate(self, src_fname, ugraph):
+class uTensorLegacyCodeGenerator(BackendPart, object):
+
+  TARGET = 'utensor'
+  PART = 'legacy_code_generator'
+
+  def __init__(self, config):
+    final_config = Configuration(self.default_config, config)
+    self.src_fname = final_config['src_fname']
+    self.params_dir = final_config['params_dir'].rstrip('/')
+    if not os.path.exists(self.params_dir):
+      os.makedirs(self.params_dir)
+    self.embed_data_dir = final_config['embed_params_dir'].rstrip('/')
+    self.model_dir = final_config['model_dir'].rstrip('/')
+    self.trans_methods = final_config['transform_methods']
+    self.save_graph = final_config['save_graph']
+    self.debug_cmt = final_config['debug_cmt']
+
+  @classmethod
+  def from_kwargs(cls, **kwargs):
+    return cls(config=kwargs)
+
+  def apply(self, ugraph):
     """Generate source and header files
     """
-    fname, _ = os.path.splitext(src_fname)
-    graph_name, _ = os.path.splitext(os.path.basename(self.model_file))
-    guard_name = fname.replace('/', '_')
-    weightheader_fname = '{}_weight.hpp'.format(fname)
-    header_snippet = ContextHeaderSnippet(guard_name, graph_name)
+    src_fname = self.src_fname
+    if src_fname == 'None':
+      src_fname = '{}.cpp'.format(ugraph.name)
+    header_snippet = ContextHeaderSnippet(
+      '_MODELS_{}'.format(ugraph.name),
+      ugraph.name
+    )
     weight_container = ContextGlobalArrayContainer()
     composer = Composer()
-    header_fname = '{}.hpp'.format(fname)
-    header_name = os.path.basename(header_fname)
-    weightheader_name = os.path.basename(weightheader_fname)
-    container = ContextSnippetsContainer(graph_name, header_name, weightheader_name)
+    header_fname = '{}.hpp'.format(ugraph.name)
+    weight_header_fname = '{}_weight.hpp'.format(ugraph.name)
+    container = ContextSnippetsContainer(ugraph.name, header_fname, weight_header_fname)
 
     opFactory = OperatorFactory()
 
     self._check_non_quantized(ugraph)
-    _logger.info("Transforming graph: %s", self.model_file)
-    def formatter(name, kwargs):
-      if kwargs:
-        return '{}({})'.format(
-          name,
-          ', '.join(['{}={!r}'.format(k, v) for k, v in kwargs.items()])
-        )
-      else:
-        return name
-    _logger.info("Transform pipeline: %s", ' -> '.join([
-      formatter(name, kwargs) for name, kwargs in self.trans_methods
-      ])
-    )
+    _logger.info("Transforming graph: %s", ugraph.name)
+    _logger.info("Transform pipeline: %s", ' -> '.join(self.trans_methods))
     quant_ugraph = self._transform_graph(ugraph,
                                          self.trans_methods)
     _logger.info('Graph transormation done')
 
     if self.save_graph:
       _logger.info('Saving transformed graph')
-      pkl_fname = "quant_{}.pkl".format(graph_name)
+      pkl_fname = "quant_{}.pkl".format(ugraph.name)
       with open(pkl_fname, 'wb') as fid:
         pickle.dump(quant_ugraph, fid)
       _logger.info('{} saved'.format(pkl_fname))
 
+    if not os.path.exists(os.path.join(self.params_dir, ugraph.name)):
+      os.makedirs(os.path.join(self.params_dir, ugraph.name))
     for op_id, op_name in enumerate(quant_ugraph.topo_order):
       op_info = quant_ugraph.ops_info[op_name]
       op_type = op_info.op_type
@@ -106,7 +97,7 @@ def formatter(name, kwargs):
         # TODO: the operator may correspond to multiple snippets (such as InlinTensor)
         # weight_container is passed to function for workaround
         snippet = opFactory.createOperatorSnippet(op_info,
-                                                  idx_dir=self.idx_dir,
+                                                  idx_dir=os.path.join(self.params_dir, ugraph.name),
                                                   embed_data_dir=self.embed_data_dir,
                                                   weight_container=weight_container,
                                                   data_manager=quant_ugraph.data_manager)
@@ -119,22 +110,47 @@ def formatter(name, kwargs):
         container.add_snippet(cmt_snippet)
     composer.add_snippet(container)
 
-    if any([method_name == 'inline' for method_name, _ in self.trans_methods]):  
-      _logger.info("Generate weight file: %s", weightheader_fname)
-      with open(weightheader_fname, "w") as wf:
+    # generate cpp/hpp files
+    if not os.path.exists(self.model_dir):
+      os.makedirs(self.model_dir)
+    if any([method == 'inline' for method in self.trans_methods]):  
+      _logger.info("Generate weight file: %s", weight_header_fname)
+      with open(os.path.join(self.model_dir, weight_header_fname), "w") as wf:
         wf.write('// Auto generated by utensor-cli\n\n')
         wf.write(weight_container.render())
     else:
-      container.remove_header('"{}"'.format(weightheader_name))
+      container.remove_header('"{}"'.format(weight_header_fname))
       
     _logger.info("Generate header file: %s", header_fname)
-    with open(header_fname, "w") as wf:
+    with open(os.path.join(self.model_dir, header_fname), "w") as wf:
       wf.write('// Auto generated by utensor-cli\n\n')
       wf.write(header_snippet.render())
     _logger.info("Generate source file: %s", src_fname)
-    with open(src_fname, "w") as wf:
+    with open(os.path.join(self.model_dir, src_fname), "w") as wf:
       wf.write('// Auto generated by utensor-cli\n\n')
       wf.write(composer.compose())
+
+  @class_property
+  def default_config(cls):
+    config = {}
+    config['src_fname'] = 'None'
+    config['params_dir'] = 'data'
+    config['embed_params_dir'] = '/fs/data'
+    config['model_dir'] = 'models'
+    config['transform_methods'] = [
+      'dropout(name_pattern=r"(dropout[_\w\d]*)/.*")',
+      'linear_reorder',
+      'quantize',
+      'conv_pool',
+      'inline',
+      'biasAdd',
+      'remove_id_op',
+      'fake_gather_v2',
+      'refcnt'
+    ]
+    config['save_graph'] = False
+    config['debug_cmt'] = False
+    return config
   
   @classmethod
   def _check_non_quantized(cls, ugraph):
diff --git a/utensor_cgen/backend/operators.py b/utensor_cgen/backend/utensor/code_generator/legacy/_operators.py
similarity index 98%
rename from utensor_cgen/backend/operators.py
rename to utensor_cgen/backend/utensor/code_generator/legacy/_operators.py
index 4f7f939a..bcc87450 100644
--- a/utensor_cgen/backend/operators.py
+++ b/utensor_cgen/backend/utensor/code_generator/legacy/_operators.py
@@ -7,24 +7,25 @@
 import numpy as np
 
 import idx2numpy as idx2np
-import tensorflow as tf
 from utensor_cgen.ir import OperationInfo, TensorInfo
 from utensor_cgen.ir.converter import (AttrValueConverter, DataTypeConverter,
                                        GenericTensorConverterMixin)
 from utensor_cgen.logger import logger
 from utensor_cgen.matcher import OpEqualityDelegate, _morphism
 from utensor_cgen.transformer.optimizer import RefCntOptimizer
-from utensor_cgen.utils import NamescopedKWArgsParser
+from utensor_cgen.utils import NamescopedKWArgsParser, LazyLoader
 
-from .snippets import *  # pylint: disable=W0401,W0614
+from utensor_cgen.backend.utensor.snippets.legacy import *  # pylint: disable=W0401,W0614
 
 __all__ = ['OperatorFactory', 'OpNotSupportedError']
+tf = LazyLoader('tensorflow')
+
 
 class OpNotSupportedError(Exception): pass
 
 
-class OperatorFactory():
-  # Can easily do something smarter
+class OperatorFactory(object):
+
   _operators = {}
 
   def createOperatorSnippet(self, op_info, **kwargs):
@@ -138,7 +139,7 @@ def build_op_info(cls, ugraph, name, value, **kwargs):
         )
       },
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow')
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
   def _tf_prepare_tensor_name(self, tensor_name):
@@ -202,7 +203,7 @@ def build_op_info(cls, ugraph, name, tensor_x, tensor_y, **kwargs):
         )
       },
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow')
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
 
@@ -265,7 +266,7 @@ def build_op_info(cls, ugraph, name, input_tensor, dtype=np.dtype('int64'), axis
       ],
       op_attr=op_attr,
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow')
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
 
@@ -350,7 +351,7 @@ def build_op_info(cls, ugraph, name, tensor, axis=-1, keepdims=False, **kwargs):
         k: AttrValueConverter.get_generic_value(v)
         for k, v in node_def.attr.items()
       },
-      backend=kwargs.get('backend', 'tensorflow'),
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
       ugraph=ugraph
     )
 
@@ -408,7 +409,7 @@ def build_op_info(cls, ugraph, name, tensor, axis=-1, keepdims=False, **kwargs):
         )
       ],
       op_type=cls.op_type,
-      backend=kwargs.get('backend', 'tensorflow'),
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
       ugraph=ugraph,
       op_attr={
         k: AttrValueConverter.get_generic_value(v)
@@ -477,7 +478,7 @@ def build_op_info(
         )
       ],
       op_type=cls.op_type,
-      backend=kwargs.get('backend', 'tensorflow'),
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
       ugraph=ugraph,
       op_attr={
         k: AttrValueConverter.get_generic_value(v)
@@ -564,7 +565,7 @@ def build_op_info(cls, ugraph, name, tensor, axis=-1, keepdims=False, **kwargs):
         )
       ],
       op_type=cls.op_type,
-      backend=kwargs.get('backend', 'tensorflow'),
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
       ugraph=ugraph,
       op_attr={
         k: AttrValueConverter.get_generic_value(v)
@@ -654,7 +655,7 @@ def build_op_info(cls, ugraph, name, tensor_x, tensor_w, **kwargs):
         )
       },
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow')
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
 
@@ -726,7 +727,7 @@ def build_op_info(cls, ugraph, name, tensor, **kwargs):
         )
       },
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow')
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
 
@@ -894,7 +895,6 @@ class _CMSIS_NN_FCOperator(_Operator):
   
   def __init__(self, op_info, **kwargs):
     _Operator.__init__(self)
-    #import pdb; pdb.set_trace()
     # Note order of inputs/outputs is preserved
     inputs = [tensor_info.name for tensor_info in op_info.input_tensors]
     output = op_info.output_tensors[0].name
@@ -972,7 +972,7 @@ def build_op_info(cls, ugraph, name, tensor_x, tensor_w, stride_height, stride_w
       op_type=cls.op_type,
       op_attr=op_attr,
       ugraph=ugraph,
-      backend=kwargs.get('backend', 'tensorflow'),
+      lib_name=kwargs.get('lib_name', 'tensorflow'),
     )
 
 @OperatorFactory.register
diff --git a/utensor_cgen/backend/utensor/code_generator/rearch/__init__.py b/utensor_cgen/backend/utensor/code_generator/rearch/__init__.py
new file mode 100644
index 00000000..45c2164e
--- /dev/null
+++ b/utensor_cgen/backend/utensor/code_generator/rearch/__init__.py
@@ -0,0 +1 @@
+from ._code_generator import uTensorRearchCodeGenerator
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/code_generator/rearch/_code_generator.py b/utensor_cgen/backend/utensor/code_generator/rearch/_code_generator.py
new file mode 100644
index 00000000..65c53e1d
--- /dev/null
+++ b/utensor_cgen/backend/utensor/code_generator/rearch/_code_generator.py
@@ -0,0 +1,170 @@
+import os
+import pickle
+import re
+from itertools import chain
+from pathlib import Path
+
+from utensor_cgen.backend.base import BackendPart
+from utensor_cgen.backend.utensor.snippets.composer import Composer
+from utensor_cgen.backend.utensor.snippets.legacy import (
+    ContextGlobalArrayContainer, WeightSnippet)
+from utensor_cgen.backend.utensor.snippets.rearch import SimpleContainer
+from utensor_cgen.backend.utensor.snippets.template_env import env
+from utensor_cgen.transformer.pipeline import TransformerPipeline
+from utensor_cgen.utils import Configuration, class_property
+
+from ._operators import OperatorFactory
+
+
+class uTensorRearchCodeGenerator(BackendPart):
+
+  TARGET = 'utensor'
+  PART = 'rearch_code_generator'
+  
+  def __init__(self, config):
+    final_config = Configuration(self.default_config, config)
+    self.src_fname = final_config['src_fname']
+    self.header_fname = final_config['header_fname']
+    self.params_dir = final_config['params_dir'].rstrip('/')
+    self.trans_methods = final_config['transform_methods']
+    self.meta_data_pool_size = final_config['meta_data_pool_size']
+    self.ram_data_pool_size = final_config['ram_data_pool_size']
+    self.model_dir = final_config['model_dir'].rstrip('/')
+    self.save_graph = final_config['save_graph']
+
+  def apply(self, ugraph):
+    src_fname = self.src_fname
+    if src_fname == 'None':
+      src_fname = '{}.cpp'.format(ugraph.name)
+    pipeline = TransformerPipeline(self.trans_methods)
+    new_ugraph = pipeline.transform(ugraph)
+    if self.save_graph:
+      with open('transformed_{}.pkl'.format(ugraph.name), 'wb') as fid:
+        pickle.dump(new_ugraph, fid)
+    # 1. find all ops required
+    ops = set()
+    placeholders = set()
+    tensor_var_map = {} # tensor name -> var name
+    for op_info in new_ugraph.ops_info.values():
+      for tensor in op_info.output_tensors:
+        tensor_var_name = re.sub(r'[:/]', '', tensor.name)
+        tensor_var_map[tensor.name] = tensor_var_name
+        if op_info.op_type == 'Placeholder':
+          placeholders.add(tensor_var_name)
+      if op_info.op_type not in ['Placeholder', 'Inline']:
+        ops.add(
+          OperatorFactory.get_opertor(op_info)
+        )
+    # 2. ops/tensors declaration
+    declare_snippets = []
+    ops_map = {} # op -> op variable name
+    for i, op in enumerate(ops):
+      op_var_name = 'op_{:03d}'.format(i)
+      ops_map[op] = op_var_name
+      declare_snippets.append(op.get_declare_snippet(op_var_name))
+    weight_snippets = []
+    for op_info in filter(lambda op_info: op_info.op_type == 'Inline', new_ugraph.ops_info.values()):
+      tensor = op_info.output_tensors[0]
+      buffer_name = 'data_{}'.format(tensor.name.replace(':', '_').replace('/', '_'))
+      weight_snippets.append(
+        WeightSnippet(
+          buffer_name,
+          tensor.dtype,
+          tensor.shape,
+          op_info.op_attr['value'].value.np_array.ravel()
+        )
+      )
+      declare_snippets.append(
+        OperatorFactory.get_opertor(op_info).get_declare_snippet(
+          tensor_var_name=tensor_var_map[tensor.name],
+          buffer_var_name=buffer_name,
+          tensor=tensor
+        )
+      )
+    # 3. evaluation snippets
+    eval_snippets = []
+    for op_name in new_ugraph.topo_order:
+      op_info = new_ugraph.ops_info[op_name]
+      if op_info.op_type in ['Placeholder', 'Inline']:
+        continue
+      op = OperatorFactory.get_opertor(op_info)
+      op_name = ops_map[op]
+      eval_snippets.append(
+        op.get_eval_snippet(op_info, op_name, tensor_var_map)
+      )
+    template_vars = {}
+    template_vars['model_name'] = ugraph.name
+    template_vars['meta_data_pool_size'] = self._compute_meta_data_size(new_ugraph)
+    template_vars['ram_data_pool_size'] = self._compute_ram_data_size(new_ugraph)
+    template_vars['placeholders'] = placeholders
+    template_vars['out_tensor_var_names'] = [
+      tensor_var_map[tensor.name] for tensor in chain(*[
+        new_ugraph.ops_info[op_name].output_tensors
+        for op_name in new_ugraph.output_nodes
+      ])
+    ]
+    # 4. write files
+    params_dir = Path(self.params_dir) / ugraph.name
+    params_dir.mkdir(parents=True, exist_ok=True)
+    weight_header_fname = None
+    if weight_snippets:
+      with (params_dir / 'params_{}.hpp'.format(ugraph.name)).open('w') as fid:
+        weight_container = ContextGlobalArrayContainer(snippets=weight_snippets)
+        fid.write(weight_container.render())
+        weight_header_fname = fid.name
+
+    # # generate the computation function
+    model_file_dir = Path(self.model_dir)
+    header_fname = self.header_fname == 'None' and '{}.hpp'.format(ugraph.name) or self.header_fname
+    container_snippet = SimpleContainer(declare_snippets=declare_snippets, eval_snippests=eval_snippets)
+    container_snippet.template_vars.update(template_vars)
+    (model_file_dir / ugraph.name).mkdir(parents=True, exist_ok=True)
+    with (model_file_dir / ugraph.name / header_fname).open('w') as fid:
+      template = env.get_template('snippets/rearch/simple.hpp')
+      fid.write(template.render(**template_vars))
+      container_snippet.add_header(fid.name)
+    if weight_header_fname:
+      container_snippet.add_header(weight_header_fname)
+    composer = Composer(snippets=[container_snippet])
+    src_fname = self.src_fname == 'None' and '{}.cpp'.format(ugraph.name) or self.src_fname
+    with (model_file_dir / ugraph.name / src_fname ).open('w') as fid:
+      fid.write(composer.compose())
+
+  @class_property
+  def default_config(cls):
+    config = {}
+    config['src_fname'] = 'None'
+    config['header_fname'] = 'None'
+    config['params_dir'] = 'data'
+    config['model_dir'] = 'models'
+    config['transform_methods'] = [
+      'dropout(name_pattern=r"(dropout[_\w\d]*)/.*")',
+      # 'linear_reorder',
+      # 'quantize',
+      # 'conv_pool',
+      'inline',
+      'biasAdd',
+      'remove_id_op',
+      'fake_gather_v2',
+      # 'refcnt'
+    ]
+    config['meta_data_pool_size'] = 'auto'
+    config['ram_data_pool_size'] = 'auto'
+    config['save_graph'] = False
+    return config
+
+  def _compute_meta_data_size(self, ugraph):
+    if self.meta_data_pool_size == 'auto':
+      # TODO: compute actual meta data size with ugraph
+      size = 256
+    else:
+      size = self.meta_data_pool_size
+    return size
+
+  def _compute_ram_data_size(self, ugraph):
+    if self.ram_data_pool_size == 'auto':
+      # TODO: compute actual ram data size with ugraph
+      size = 256
+    else:
+      size = self.ram_data_pool_size
+    return size
diff --git a/utensor_cgen/backend/utensor/code_generator/rearch/_operators.py b/utensor_cgen/backend/utensor/code_generator/rearch/_operators.py
new file mode 100644
index 00000000..9f34857a
--- /dev/null
+++ b/utensor_cgen/backend/utensor/code_generator/rearch/_operators.py
@@ -0,0 +1,127 @@
+from six import with_metaclass
+
+from utensor_cgen.backend.utensor.snippets._types import NP_TYPES_MAP
+from utensor_cgen.backend.utensor.snippets.rearch import (AddOpEvalSnippet,
+                                                          DeclareOpSnippet,
+                                                          RomTensorSnippet)
+
+__all__ = ['OperatorFactory', 'OpNotSupportedError']
+
+
+class OpNotSupportedError(Exception): pass
+
+
+class OperatorFactory(object):
+
+  _operators = {}
+
+  @classmethod
+  def get_opertor(cls, op_info):
+    op_type = op_info.op_type
+    op_cls = cls._operators.get(op_type)
+    if op_cls is None:
+      raise OpNotSupportedError(
+        '{} not supported in utensor_cgen'.format(op_type)
+      )
+    return op_cls(op_info)
+
+  @classmethod
+  def register(cls, op_cls):
+    cls._operators[op_cls.op_type] = op_cls
+    return op_cls
+
+  @classmethod
+  def support_op_types(cls):
+    """Return the set of all supported ops
+    """
+    return set(cls._operators.keys())
+
+  @classmethod
+  def is_supported(cls, op_type):
+    if op_type != 'Placeholder' and op_type not in cls._operators:
+      return False
+    return True
+
+
+class _OperatorMeta(type):
+
+  def __new__(mcls, name, bases, attrib):
+    attrib['_cache'] = {}
+    cls = type.__new__(mcls, name, bases, attrib)
+    return cls
+
+
+class _Operator(with_metaclass(_OperatorMeta), object):
+
+  def __new__(cls, op_info):
+    in_dtypes = tuple(t.dtype for t in op_info.input_tensors)
+    out_dtypes = tuple(t.dtype for t in op_info.output_tensors)
+    type_signature = (in_dtypes, out_dtypes)
+    if type_signature not in cls._cache:
+      self = object.__new__(cls)
+      self.in_dtypes = in_dtypes
+      self.out_dtypes = out_dtypes
+      cls._cache[type_signature] = self
+    return cls._cache[type_signature]
+
+  def get_declare_snippet(self, op_var_name, **kwargs):
+    raise NotImplementedError(
+      'base get_declare_snippet invoked: {}'.format(type(self))
+    )
+
+  def get_eval_snippet(self, op_info, op_name, tensor_var_map, **kwargs):
+    raise NotImplementedError(
+      'base get_eval_snippet invoked: {}'.format(type(self))
+    )
+
+
+@OperatorFactory.register
+class _AddOperator(_Operator):
+
+  op_type = 'AddOperator'
+
+  def get_declare_snippet(self, op_var_name):
+    snippet = DeclareOpSnippet(
+      op_type=self.op_type,
+      dtypes=[NP_TYPES_MAP[self.in_dtypes[0]].tensor_type_str],
+      op_var_name=op_var_name,
+    )
+    return snippet
+
+  def get_eval_snippet(self, op_info, op_name, tensor_var_map):
+    snippet = AddOpEvalSnippet(
+      op_info=op_info,
+      op_name=op_name,
+      tensor_var_map=tensor_var_map,
+      dtypes=[op_info.input_tensors[0].dtype]
+    )
+    return snippet
+
+
+@OperatorFactory.register
+class _MatmulOperator(_Operator):
+
+  op_type = 'MatrixMultOperator'
+
+
+@OperatorFactory.register
+class _ConvOperator(_Operator):
+
+  op_type = 'ConvOperator'
+
+
+@OperatorFactory.register
+class _InlineOperator(_Operator):
+
+  op_type = 'Inline'
+
+  def __init__(self, op_info):
+    self._tensor = op_info.output_tensors[0]
+
+  def get_declare_snippet(self, tensor_var_name, buffer_var_name, tensor):
+    snippet = RomTensorSnippet(
+      tensor_var_name=tensor_var_name,
+      buffer_var_name=buffer_var_name,
+      tensor=tensor
+    )
+    return snippet
diff --git a/utensor_cgen/backend/utensor/snippets/__init__.py b/utensor_cgen/backend/utensor/snippets/__init__.py
new file mode 100644
index 00000000..81c3b0fd
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/__init__.py
@@ -0,0 +1 @@
+from .template_env import env
\ No newline at end of file
diff --git a/utensor_cgen/backend/snippets/_base.py b/utensor_cgen/backend/utensor/snippets/_base.py
similarity index 84%
rename from utensor_cgen/backend/snippets/_base.py
rename to utensor_cgen/backend/utensor/snippets/_base.py
index 96b5f00b..0d03add4 100644
--- a/utensor_cgen/backend/snippets/_base.py
+++ b/utensor_cgen/backend/utensor/snippets/_base.py
@@ -2,6 +2,8 @@
 from abc import ABCMeta
 from copy import deepcopy
 
+from utensor_cgen.utils import MUST_OVERWRITEN
+
 from .template_env import env as _env
 
 __all__ = ["Snippet", "SnippetContainerBase"]
@@ -9,14 +11,14 @@
 
 class SnippetBase(object):
   __metaclass__ = ABCMeta
-  __template_name__ = None
-  __headers__ = None
+  __template_name__ = MUST_OVERWRITEN
+  __headers__ = MUST_OVERWRITEN
 
   def __init__(self):
-    if self.__template_name__ is None:
-      raise ValueError('No {}.__template_name__ not defined'.format(type(self)))
-    if self.__headers__ is None:
-      raise ValueError('No {}.__headers__ not defined'.format(type(self)))
+    if self.__template_name__ is MUST_OVERWRITEN:
+      raise ValueError('must overwrite {}.__template_name__'.format(type(self)))
+    if self.__headers__ is MUST_OVERWRITEN:
+      raise ValueError('must overwrite {}.__headers__'.format(type(self)))
     if not isinstance(self.__headers__, set):
       raise ValueError('__headers__ should be of type set, get {}'.format(type(self.__headers__)))
     self.template_vars = {}
diff --git a/utensor_cgen/backend/utensor/snippets/_types.py b/utensor_cgen/backend/utensor/snippets/_types.py
new file mode 100644
index 00000000..24f875ef
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/_types.py
@@ -0,0 +1,97 @@
+# -*- coding:utf8 -*-
+from collections import namedtuple
+
+import numpy as np
+
+from utensor_cgen.utils import LazyLoader
+
+tf = LazyLoader('tensorflow')
+
+
+class NumpyTypesMap(object):
+  _obj = None
+  _NP_TYPES_MAP = {}
+  _inited = False
+
+  def __new__(cls):
+    if cls._obj is None:
+      self = object.__new__(cls)
+      cls._obj = self
+    return cls._obj
+
+  def __getitem__(self, key):
+    cls = type(self)
+    cls._init()
+    return cls._NP_TYPES_MAP[key]
+  
+  def __setitem__(self, key, value):
+    cls = type(self)
+    cls._init()
+    cls._NP_TYPES_MAP[key] = value
+
+  def __contains__(self, key):
+    cls = type(self)
+    cls._init()
+    return key in cls._NP_TYPES_MAP
+  
+  @classmethod
+  def _init(cls):
+    if not cls._inited:
+      _TYPE_MAP_VALUE = namedtuple("_TYPE_MAP_VALUE", ["importer_type_str", "tensor_type_str"])
+      cls._NP_TYPES_MAP = {
+        np.dtype(tf.float32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="float",
+                                                            tensor_type_str="float"),
+        np.dtype(tf.qint8.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="byte", 
+                                                          tensor_type_str="uint8_t"),
+        np.dtype(tf.int32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
+                                                          tensor_type_str="int"),
+        np.dtype(tf.int64.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
+                                                          tensor_type_str="int"),
+        np.dtype(tf.quint8.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="ubyte",
+                                                            tensor_type_str="uint8_t"),
+        np.dtype(tf.qint32.as_numpy_dtype): _TYPE_MAP_VALUE(importer_type_str="int", 
+                                                            tensor_type_str="int"),
+        np.dtype('uint16'): _TYPE_MAP_VALUE(importer_type_str="ushort",
+                                            tensor_type_str="uint16_t"),
+        np.dtype('int8'): _TYPE_MAP_VALUE(importer_type_str="int8",
+                                          tensor_type_str="q7_t"),
+      }
+      cls._inited = True
+
+NP_TYPES_MAP = NumpyTypesMap()
+
+class Numpy2uTensorTypesMap(object):
+  _obj = None
+  _NP_TYPES_MAP = {}
+  _inited = False
+
+  def __new__(cls):
+    if cls._obj is None:
+      cls._obj = object.__new__(cls)
+    return cls._obj
+
+  def __getitem__(self, key):
+    cls = type(self)
+    cls._init()
+    return cls._NP_TYPES_MAP.get(key, 'undefined')
+
+  def __contains__(self, key):
+    cls = type(self)
+    cls._init()
+    return key in cls._NP_TYPES_MAP
+  
+  @classmethod
+  def _init(cls):
+    if not cls._inited:
+      cls._NP_TYPES_MAP = {
+        np.dtype('int8'): 'i8',
+        np.dtype('uint8'): 'u8',
+        np.dtype('int16'): 'i16',
+        np.dtype('uint16'): 'u16',
+        np.dtype('int32'): 'i32',
+        np.dtype('uint32'): 'u32',
+        np.dtype('float32'): 'flt',
+      }
+      cls._inited = True
+
+UTENSOR_TYPES_MAP = Numpy2uTensorTypesMap()
\ No newline at end of file
diff --git a/utensor_cgen/backend/snippets/composer.py b/utensor_cgen/backend/utensor/snippets/composer.py
similarity index 64%
rename from utensor_cgen/backend/snippets/composer.py
rename to utensor_cgen/backend/utensor/snippets/composer.py
index 80e533cb..3da608ff 100644
--- a/utensor_cgen/backend/snippets/composer.py
+++ b/utensor_cgen/backend/utensor/snippets/composer.py
@@ -1,7 +1,7 @@
 # -*- coding:utf8 -*-
 import re
 
-from ._snippets import Snippet, SnippetContainerBase
+from ._base import Snippet, SnippetContainerBase, SnippetBase
 
 _STD_PATTERN = re.compile(r'^<[\w]+(.h|.hpp)?>$')
 
@@ -11,11 +11,9 @@ class Composer(object):
   def __init__(self, snippets=None):
     if snippets is None:
       snippets = []
+    self._snippets = []
     for snp in snippets:
-      if not isinstance(snp, (Snippet, SnippetContainerBase)):
-        msg = "expecting Snippet/SnippetContainerBase objects, get {}".format(type(snp))
-        raise TypeError(msg)
-    self._snippets = snippets
+      self.add_snippet(snp)
     self._cached = False
     self._text = ""
 
@@ -29,7 +27,7 @@ def compose(self):
     return self._text
 
   def add_snippet(self, snippet):
-    if not isinstance(snippet, (Snippet, SnippetContainerBase)):
+    if not isinstance(snippet, (SnippetBase, Snippet, SnippetContainerBase)):
       msg = "expecting Snippet/SnippetContainerBase object, get {}".format(type(snippet))
       raise ValueError(msg)
     self._cached = False
@@ -39,8 +37,8 @@ def _compose_header(self):
     unique_headers = set([])
     for snp in self._snippets:
       unique_headers.update(snp.headers)
-    headers = [(header, 0) if _STD_PATTERN.match(header) else (header, 1) for header in unique_headers]
-    headers = [t[0] for t in sorted(headers, key=lambda t: t[1], reverse=True)]
+    headers = [(0, header) if _STD_PATTERN.match(header) else (1, header) for header in unique_headers]
+    headers = [t[1] for t in sorted(headers, reverse=True)]
     for header in headers:
       self._text += "#include {}\n".format(header)
     self._text += "\n\n"
diff --git a/utensor_cgen/backend/utensor/snippets/legacy/__init__.py b/utensor_cgen/backend/utensor/snippets/legacy/__init__.py
new file mode 100644
index 00000000..f2204d0b
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/legacy/__init__.py
@@ -0,0 +1 @@
+from ._snippets import *
\ No newline at end of file
diff --git a/utensor_cgen/backend/snippets/_snippets.py b/utensor_cgen/backend/utensor/snippets/legacy/_snippets.py
similarity index 92%
rename from utensor_cgen/backend/snippets/_snippets.py
rename to utensor_cgen/backend/utensor/snippets/legacy/_snippets.py
index dff12c67..f798012a 100644
--- a/utensor_cgen/backend/snippets/_snippets.py
+++ b/utensor_cgen/backend/utensor/snippets/legacy/_snippets.py
@@ -1,11 +1,10 @@
 # -*- coding:utf8 -*-
 import numpy as np
 
-from ._base import Snippet, SnippetContainerBase  # pylint: disable=W0611
-from ._types import NP_TYPES_MAP
+from .._base import Snippet, SnippetContainerBase  # pylint: disable=W0611
+from .._types import NP_TYPES_MAP
 
-__all__ = ["Snippet", "SnippetContainerBase",
-           "CreateTensorIdxSnippet", "CreateTensorNewSnippet",
+__all__ = ["CreateTensorIdxSnippet", "CreateTensorNewSnippet",
            "AddOpSnippet", "MinOpSnippet", "MaxOpSnippet",
            "ArgMaxOpSnippet", "DequantizeOpSnippet",
            "QuantizedMaxPoolSnippet", "MaxPoolSnippet",
@@ -26,7 +25,7 @@
 
 # TODO: Better abstraction, i.e a better backend for code generation
 class CreateTensorIdxSnippet(Snippet):
-  __template_name__ = "snippets/create_tensor_idx.cpp"
+  __template_name__ = "snippets/legacy/create_tensor_idx.cpp"
   __headers__ = set(['"uTensor/loaders/tensorIdxImporter.hpp"',
                      '"uTensor/core/context.hpp"',
                      '"uTensor/core/tensor.hpp"'])
@@ -56,7 +55,7 @@ def __init__(self, data_dir, tensor_name, np_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class CreateTensorRamSnippet(Snippet):
-  __template_name__ = "snippets/create_tensor_new.cpp"
+  __template_name__ = "snippets/legacy/create_tensor_new.cpp"
   __headers__ = set(['"uTensor/core/context.hpp"',
                      '"uTensor/core/tensor.hpp"'])
 
@@ -87,7 +86,7 @@ def _to_shape_str(self, shape):
 
 
 class CreateTensorBinarySnippet(Snippet):
-  __template_name__ = "snippets/create_tensor_binary.cpp"
+  __template_name__ = "snippets/legacy/create_tensor_binary.cpp"
   __headers__ = set(['"uTensor/core/context.hpp"',
                      '"uTensor/core/tensor.hpp"'])
 
@@ -124,7 +123,7 @@ def _to_shape_str(self, shape):
 
 
 class CreateTensorNewSnippet(Snippet):
-  __template_name__ = "snippets/create_tensor_new.cpp"
+  __template_name__ = "snippets/legacy/create_tensor_new.cpp"
   __headers__ = set(['"uTensor/core/context.hpp"', '"uTensor/core/tensor.hpp"'])
 
   def __init__(self, tensor_name, np_dtype,
@@ -170,7 +169,7 @@ def _permute_args(args, perm=None):
 
 
 class AddOpSnippet(Snippet):
-  __template_name__ = "snippets/add_op.cpp"
+  __template_name__ = "snippets/legacy/add_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, output, np_dtype,
@@ -187,7 +186,7 @@ def __init__(self, inputs, output, np_dtype,
 
 
 class MinOpSnippet(Snippet):
-  __template_name__ = "snippets/min_op.cpp"
+  __template_name__ = "snippets/legacy/min_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, output, out_dtype,
@@ -207,7 +206,7 @@ def __init__(self, inputs, output, out_dtype,
 
 
 class MaxOpSnippet(Snippet):
-  __template_name__ = "snippets/max_op.cpp"
+  __template_name__ = "snippets/legacy/max_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, output, out_dtype,
@@ -226,7 +225,7 @@ def __init__(self, inputs, output, out_dtype,
     self.template_vars["address"] = address
 
 class MaxPoolSnippet(Snippet):
-  __template_name__ = "snippets/max_pool_op.cpp"
+  __template_name__ = "snippets/legacy/max_pool_op.cpp"
   __headers__ = set(['"uTensor/ops/NnOps.hpp"'])
 
   def __init__(self, inputs, output, dtype,
@@ -250,7 +249,7 @@ def __init__(self, inputs, output, dtype,
 
 
 class QuantizedMaxPoolSnippet(Snippet):
-  __template_name__ = "snippets/qmax_pool_op.cpp"
+  __template_name__ = "snippets/legacy/qmax_pool_op.cpp"
   __headers__ = set(['"uTensor/ops/NnOps.hpp"'])
 
   def __init__(self, inputs, outputs, dtype,
@@ -279,7 +278,7 @@ def __init__(self, inputs, outputs, dtype,
 
 
 class ArgMaxOpSnippet(Snippet):
-  __template_name__ = "snippets/argmax_op.cpp"
+  __template_name__ = "snippets/legacy/argmax_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, output, in_dtype, out_dtype,
@@ -298,7 +297,7 @@ def __init__(self, inputs, output, in_dtype, out_dtype,
 
 
 class DequantizeOpSnippet(Snippet):
-  __template_name__ = "snippets/dequantize_op.cpp"
+  __template_name__ = "snippets/legacy/dequantize_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, out_dtype,
@@ -315,7 +314,7 @@ def __init__(self, inputs, output, out_dtype,
     self.template_vars["address"] = address
 
 class MatMulOpSnippet(Snippet):
-  __template_name__ = "snippets/matmul_op.cpp"
+  __template_name__ = "snippets/legacy/matmul_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, output, x_dtype, w_dtype, out_dtype,
@@ -333,7 +332,7 @@ def __init__(self, inputs, output, x_dtype, w_dtype, out_dtype,
 
 
 class QuantizedMatMulOpSnippet(Snippet):
-  __template_name__ = "snippets/qmatmul_op.cpp"
+  __template_name__ = "snippets/legacy/qmatmul_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
@@ -361,7 +360,7 @@ def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
 
 
 class QuantizedAddOpSnippet(Snippet):
-  __template_name__ = "snippets/qadd_op.cpp"
+  __template_name__ = "snippets/legacy/qadd_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
@@ -388,7 +387,7 @@ def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
     self.template_vars['address'] = address
 
 class QuantizedMulOpSnippet(Snippet):
-  __template_name__ = "snippets/qmul_op.cpp"
+  __template_name__ = "snippets/legacy/qmul_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
@@ -414,7 +413,7 @@ def __init__(self, inputs, outputs, x_dtype, w_dtype, out_dtype,
 
 
 class QuantizeV2OpSnippet(Snippet):
-  __template_name__ = "snippets/quantV2_op.cpp"
+  __template_name__ = "snippets/legacy/quantV2_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, outputs, out_dtype,
@@ -437,7 +436,7 @@ def __init__(self, inputs, outputs, out_dtype,
 
 
 class ReluOpSnippet(Snippet):
-  __template_name__ = "snippets/relu_op.cpp"
+  __template_name__ = "snippets/legacy/relu_op.cpp"
   __headers__ = set(['"uTensor/ops/NnOps.hpp"'])
 
   def __init__(self, inputs, output, in_dtype, out_dtype,
@@ -453,7 +452,7 @@ def __init__(self, inputs, output, in_dtype, out_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class QuantizedReluOpSnippet(Snippet):
-  __template_name__ = "snippets/qrelu_op.cpp"
+  __template_name__ = "snippets/legacy/qrelu_op.cpp"
   __headers__ = set(['"uTensor/ops/NnOps.hpp"'])
 
   def __init__(self, inputs, outputs, in_dtype, out_dtypes, qout_dtype,
@@ -477,7 +476,7 @@ def __init__(self, inputs, outputs, in_dtype, out_dtypes, qout_dtype,
     self.template_vars["address"] = address
 
 class RequantizationRangeOpSnippet(Snippet):
-  __template_name__ = "snippets/requant_range_op.cpp"
+  __template_name__ = "snippets/legacy/requant_range_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, outputs, out_dtype,
@@ -500,7 +499,7 @@ def __init__(self, inputs, outputs, out_dtype,
 
 
 class RequantizeOpSnippet(Snippet):
-  __template_name__ = "snippets/requant_op.cpp"
+  __template_name__ = "snippets/legacy/requant_op.cpp"
   __headers__ = set(['"uTensor/ops/MathOps.hpp"'])
 
   def __init__(self, inputs, outputs, qout_dtype, range_dtype,
@@ -528,7 +527,7 @@ def __init__(self, inputs, outputs, qout_dtype, range_dtype,
 
 
 class StridedSliceOpSnippet(Snippet):
-  __template_name__ = "snippets/strided_slice_op.cpp"
+  __template_name__ = "snippets/legacy/strided_slice_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, dtype, out_dtype,
@@ -550,7 +549,7 @@ def __init__(self, inputs, output, dtype, out_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class PackOpSnippet(Snippet):
-  __template_name__ = "snippets/pack_op.cpp"
+  __template_name__ = "snippets/legacy/pack_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, dtype, out_dtype, N, axis,
@@ -568,7 +567,7 @@ def __init__(self, inputs, output, dtype, out_dtype, N, axis,
     self.template_vars["to_eval"] = to_eval
 
 class ShapeOpSnippet(Snippet):
-  __template_name__ = "snippets/shape_op.cpp"
+  __template_name__ = "snippets/legacy/shape_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, out_dtype,
@@ -583,7 +582,7 @@ def __init__(self, inputs, output, out_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class SoftmaxOpSnippet(Snippet):
-  __template_name__ = "snippets/softmax_op.cpp"
+  __template_name__ = "snippets/legacy/softmax_op.cpp"
   __headers__ = set(['"uTensor/ops/NnOps.hpp"'])
 
   def __init__(self, input_tname, output_tname,
@@ -603,7 +602,7 @@ def __init__(self, input_tname, output_tname,
 
 
 class ReshapeOpSnippet(Snippet):
-  __template_name__ = "snippets/reshape_op.cpp"
+  __template_name__ = "snippets/legacy/reshape_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, dtype,
@@ -621,7 +620,7 @@ def __init__(self, inputs, output, dtype,
 
 
 class QuantizedReshapeOpSnippet(Snippet):
-  __template_name__ = "snippets/qreshape_op.cpp"
+  __template_name__ = "snippets/legacy/qreshape_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, outputs,
@@ -635,7 +634,7 @@ def __init__(self, inputs, outputs,
     self.template_vars["to_eval"] = to_eval
 
 class CMSISNNFCOpSnippet(Snippet):
-  __template_name__ = "snippets/cmsis_nn_fc_op.cpp"
+  __template_name__ = "snippets/legacy/cmsis_nn_fc_op.cpp"
   __headers__ = set(['"uTensor/ops/cmsis_ops/FullyConnectedOps.hpp"'])
 
   def __init__(self, inputs, output, in_dtypes, out_dtype,
@@ -651,7 +650,7 @@ def __init__(self, inputs, output, in_dtypes, out_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class Conv2DOpSnippet(Snippet):
-  __template_name__ = "snippets/conv2d_op.cpp"
+  __template_name__ = "snippets/legacy/conv2d_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, output, strides, padding,
@@ -671,7 +670,7 @@ def __init__(self, inputs, output, strides, padding,
     self.template_vars["to_eval"] = to_eval
 
 class FusedConv2DMaxpoolOpSnippet(Snippet):
-  __template_name__ = "snippets/fused_conv2d_maxpool_op.cpp"
+  __template_name__ = "snippets/legacy/fused_conv2d_maxpool_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, output, strides, ksize, padding,
@@ -692,7 +691,7 @@ def __init__(self, inputs, output, strides, ksize, padding,
     self.template_vars["to_eval"] = to_eval
 
 class QuantizedFusedConv2DMaxpoolOpSnippet(Snippet):
-  __template_name__ = "snippets/quantized_fused_conv2d_maxpool_op.cpp"
+  __template_name__ = "snippets/legacy/quantized_fused_conv2d_maxpool_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, outputs, strides, ksize, padding,
@@ -717,7 +716,7 @@ def __init__(self, inputs, outputs, strides, ksize, padding,
     self.template_vars["to_eval"] = to_eval
 
 class Conv2DQuantOpSnippet(Snippet):
-  __template_name__ = "snippets/qconv2d_op.cpp"
+  __template_name__ = "snippets/legacy/qconv2d_op.cpp"
   __headers__ = set(['"uTensor/ops/MatrixOps.hpp"'])
 
   def __init__(self, inputs, outputs, strides, padding,
@@ -742,7 +741,7 @@ def __init__(self, inputs, outputs, strides, padding,
     self.template_vars["to_eval"] = to_eval
 
 class Uint8Q7OriginSnippet(Snippet):
-  __template_name__ = "snippets/cmsis_uint8q7origin_op.cpp"
+  __template_name__ = "snippets/legacy/cmsis_uint8q7origin_op.cpp"
   __headers__ = set(['"uTensor/ops/cmsis_ops/supportOps.hpp"'])
 
   def __init__(self, inputs, output,
@@ -756,7 +755,7 @@ def __init__(self, inputs, output,
     self.template_vars["to_eval"] = to_eval
 
 class QuantRangeForMultiplicationSnippet(Snippet):
-  __template_name__ = "snippets/quant_range_for_multiplication_op.cpp"
+  __template_name__ = "snippets/legacy/quant_range_for_multiplication_op.cpp"
   __headers__ = set(['"uTensor/ops/cmsis_ops/supportOps.hpp"'])
 
   def __init__(self, inputs, outputs, out_dtype,
@@ -776,7 +775,7 @@ def __init__(self, inputs, outputs, out_dtype,
     self.template_vars["to_eval"] = to_eval
 
 class CommentSnippet(Snippet):
-  __template_name__ = "snippets/comments.cpp"
+  __template_name__ = "snippets/legacy/comments.cpp"
   __headers__ = set([])
 
   def __init__(self, comments):
@@ -785,7 +784,7 @@ def __init__(self, comments):
 
 
 class ContextHeaderSnippet(Snippet):
-  __template_name__ = "snippets/get_ctx.hpp"
+  __template_name__ = "snippets/legacy/get_ctx.hpp"
   __headers__ = set(['"uTensor/core/context.hpp"', '"uTensor/core/tensor.hpp"'])
 
   def __init__(self, guard_name, graph_name, placeholders=None):
@@ -797,7 +796,7 @@ def __init__(self, guard_name, graph_name, placeholders=None):
     self.template_vars["placeholders"] = placeholders
 
 class WeightSnippet(Snippet):
-  __template_name__ = "snippets/weight_snippet.hpp"
+  __template_name__ = "snippets/legacy/weight_snippet.hpp"
   __headers__ = set([])
 
   def __init__(self, inline_name, type, shape, value):
@@ -810,7 +809,7 @@ def __init__(self, inline_name, type, shape, value):
 
 
 class ContextGlobalArrayContainer(SnippetContainerBase):
-  __template_name__ = "containers/weight_header.hpp"
+  __template_name__ = "containers/legacy/weight_header.hpp"
   __headers__ = set([])
 
   def __init__(self, snippets=None):
@@ -818,7 +817,7 @@ def __init__(self, snippets=None):
 
 
 class ContextSnippetsContainer(SnippetContainerBase):
-  __template_name__ = "containers/get_ctx.cpp"
+  __template_name__ = "containers/legacy/get_ctx.cpp"
   __headers__ = set([])
 
   def __init__(self,
@@ -840,7 +839,7 @@ def __init__(self,
     self.add_header('"{}"'.format(ctx_weightheader_name))
 
 class GatherOpSnippet(Snippet):
-  __template_name__ = "snippets/gather_op.cpp"
+  __template_name__ = "snippets/legacy/gather_op.cpp"
   __headers__ = set(['"uTensor/ops/ArrayOps.hpp"'])
 
   def __init__(self, inputs, output, np_dtype,
diff --git a/utensor_cgen/backend/utensor/snippets/rearch/__init__.py b/utensor_cgen/backend/utensor/snippets/rearch/__init__.py
new file mode 100644
index 00000000..f2204d0b
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/rearch/__init__.py
@@ -0,0 +1 @@
+from ._snippets import *
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py b/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py
new file mode 100644
index 00000000..552469a6
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/rearch/_snippets.py
@@ -0,0 +1,117 @@
+from utensor_cgen.backend.utensor.snippets._types import UTENSOR_TYPES_MAP, NP_TYPES_MAP
+from utensor_cgen.backend.utensor.snippets._base import Snippet, SnippetBase
+
+__all__ = ['RomTensorSnippet', 'DeclareOpSnippet', 'AddOpEvalSnippet', 'SimpleContainer']
+
+class _SnippetBase(Snippet):
+  __headers__ = set(['"uTensor/uTensor.hpp"'])
+
+
+class RomTensorSnippet(_SnippetBase):
+  __template_name__ = 'snippets/rearch/declare_rom_tensor.cpp'
+
+  def __init__(self, tensor_var_name, buffer_var_name, tensor):
+    Snippet.__init__(self)
+    shape = tensor.shape or [1]
+    self.template_vars = {
+      'tensor_var_name': tensor_var_name,
+      'shape': shape,
+      'buffer_var_name': buffer_var_name,
+      'utensor_dtype': UTENSOR_TYPES_MAP[tensor.dtype]
+    }
+
+
+class DeclareOpSnippet(_SnippetBase):
+  __template_name__ = 'snippets/rearch/declare_op.cpp'
+
+  def __init__(self, op_type, dtypes, op_var_name):
+    Snippet.__init__(self)
+    self.template_vars['op_type'] = op_type
+    self.template_vars['dtypes'] = dtypes
+    self.template_vars['op_var_name'] = op_var_name
+
+
+class OpEvalSnippet(_SnippetBase):
+  __template_name__ = 'snippets/rearch/eval_op.cpp'
+  __inputs__ = []
+  __outputs__ = []
+  
+
+  def __init__(self, op_info, op_name, tensor_var_map, dtypes):
+    Snippet.__init__(self)
+    input_map = {
+      name: tensor_var_map[tensor.name]
+      for name, tensor in zip(self.__inputs__, op_info.input_tensors)
+    }
+    output_map = {
+      name: tensor_var_map[tensor.name]
+      for name, tensor in zip(self.__outputs__, op_info.output_tensors)
+    }
+    out_shapes_map = {
+      tensor_var_map[tensor.name]: tensor.shape or [1]
+      for tensor in op_info.output_tensors
+    }
+    out_dtypes_map = {
+      tensor_var_map[tensor.name]: UTENSOR_TYPES_MAP[tensor.dtype]
+      for tensor in op_info.output_tensors
+    }
+    utensor_dtypes = [NP_TYPES_MAP[dtype].tensor_type_str for dtype in dtypes]
+    if utensor_dtypes:
+      op_type = '{}<{}>'.format(op_info.op_type, ', '.join(utensor_dtypes))
+    else:
+      op_type = op_info.op_type
+    self.template_vars['op_type'] = op_type
+    self.template_vars['op_name'] = op_name
+    self.template_vars['input_map'] = input_map
+    self.template_vars['output_map'] = output_map
+    self.template_vars['out_shapes_map'] = out_shapes_map
+    self.template_vars['out_dtypes_map'] = out_dtypes_map
+
+
+class AddOpEvalSnippet(OpEvalSnippet):
+  __inputs__ = ['a', 'b']
+  __outputs__ = ['c']
+
+
+class SimpleContainer(SnippetBase):
+  __headers__ = set(['"uTensor/uTensor.hpp"', "<vector>"])
+  __template_name__ = 'containers/rearch/simple.cpp'
+
+  def __init__(self, declare_snippets=None, eval_snippests=None):
+    if declare_snippets is None:
+      declare_snippets = []
+    if eval_snippests is None:
+      eval_snippests = []
+    SnippetBase.__init__(self)
+    self._declare_snippets = []
+    self._eval_snippests = []
+    for snp in declare_snippets:
+      self.add_declare_snippet(snp)
+    for snp in eval_snippests:
+      self.add_eval_snippet(snp)
+
+  def add_declare_snippet(self, snippet):
+    self.__headers__.update(snippet.headers)
+    self._declare_snippets.append(snippet)
+  
+  def add_eval_snippet(self, snippet):
+    self.__headers__.update(snippet.headers)
+    self._eval_snippests.append(snippet)
+  
+  def add_header(self, header, *headers):
+    self._add_header(header)
+    for header in headers:
+      self._add_header(header)
+    return self
+  
+  def _add_header(self, header):
+    if not header.startswith('"') and not header.startswith("<"):
+      header = '"{}"'.format(header)
+    self.__headers__.add(header)
+  
+  def render(self):
+    return self.template.render(
+      declare_snippets=self._declare_snippets,
+      eval_snippets=self._eval_snippests,
+      **self.template_vars
+    )
diff --git a/utensor_cgen/backend/snippets/template_env.py b/utensor_cgen/backend/utensor/snippets/template_env.py
similarity index 53%
rename from utensor_cgen/backend/snippets/template_env.py
rename to utensor_cgen/backend/utensor/snippets/template_env.py
index f033e30b..62de4790 100644
--- a/utensor_cgen/backend/snippets/template_env.py
+++ b/utensor_cgen/backend/utensor/snippets/template_env.py
@@ -1,12 +1,14 @@
 # -*- coding:utf8 -*-
-from jinja2 import Environment, PackageLoader
+import os
+from jinja2 import Environment, FileSystemLoader
 
-_loader = PackageLoader('utensor_cgen', 'backend/snippets/templates')
+_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'templates/')
+_loader = FileSystemLoader(searchpath=_dir)
 
 env = Environment(loader=_loader, trim_blocks=True, lstrip_blocks=True)
 env.globals.update(zip=zip)
 
-del _loader
+del _loader, _dir
 
 # useful references
 # - https://gist.github.com/wrunk/1317933/d204be62e6001ea21e99ca0a90594200ade2511e
diff --git a/utensor_cgen/backend/snippets/templates/containers/get_ctx.cpp b/utensor_cgen/backend/utensor/snippets/templates/containers/legacy/get_ctx.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/containers/get_ctx.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/containers/legacy/get_ctx.cpp
diff --git a/utensor_cgen/backend/snippets/templates/containers/weight_header.hpp b/utensor_cgen/backend/utensor/snippets/templates/containers/legacy/weight_header.hpp
similarity index 75%
rename from utensor_cgen/backend/snippets/templates/containers/weight_header.hpp
rename to utensor_cgen/backend/utensor/snippets/templates/containers/legacy/weight_header.hpp
index e1d89bcb..a77f1341 100644
--- a/utensor_cgen/backend/snippets/templates/containers/weight_header.hpp
+++ b/utensor_cgen/backend/utensor/snippets/templates/containers/legacy/weight_header.hpp
@@ -1,3 +1,5 @@
+#include <stdint.h>
+
 {% for snippet in snippets%}
 {{snippet.render()}}
 {% endfor %}
diff --git a/utensor_cgen/backend/utensor/snippets/templates/containers/rearch/simple.cpp b/utensor_cgen/backend/utensor/snippets/templates/containers/rearch/simple.cpp
new file mode 100644
index 00000000..fb1c60c3
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/containers/rearch/simple.cpp
@@ -0,0 +1,20 @@
+using namespace uTensor;
+
+{%for snippet in declare_snippets%}
+{{snippet.render()}}
+{%endfor%}
+localCircularArenaAllocator<{{meta_data_pool_size}}> meta_allocator;
+localCircularArenaAllocator<{{ram_data_pool_size}}> ram_allocator;
+
+void compute_{{model_name}}({%for pl in placeholders%}Tensor& {{pl}}, {%endfor%}std::vector<Tensor>& outputs){
+    Context::get_default_context()->set_metadata_allocator(&meta_allocator);
+    Context::get_default_context()->set_ram_data_allocator(&ram_allocator);
+
+    {%for snippet in eval_snippets%}
+    {{snippet.render()}}
+
+    {%endfor%}
+    {%for out_var in out_tensor_var_names%}
+    outputs.push_back({{out_var}});
+    {%endfor%}
+}
diff --git a/utensor_cgen/backend/snippets/templates/snippets/add_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/add_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/add_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/add_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/argmax_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/argmax_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/argmax_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/argmax_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/cmsis_nn_fc_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/cmsis_nn_fc_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/cmsis_nn_fc_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/cmsis_nn_fc_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/cmsis_uint8q7origin_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/cmsis_uint8q7origin_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/cmsis_uint8q7origin_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/cmsis_uint8q7origin_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/comments.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/comments.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/comments.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/comments.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/conv2d_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/conv2d_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/conv2d_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/conv2d_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/create_tensor_binary.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_binary.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/create_tensor_binary.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_binary.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/create_tensor_idx.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_idx.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/create_tensor_idx.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_idx.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/create_tensor_new.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_new.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/create_tensor_new.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/create_tensor_new.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/dequantize_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/dequantize_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/dequantize_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/dequantize_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/fused_conv2d_maxpool_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/fused_conv2d_maxpool_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/fused_conv2d_maxpool_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/fused_conv2d_maxpool_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/gather_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/gather_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/gather_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/gather_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/get_ctx.hpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/get_ctx.hpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/get_ctx.hpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/get_ctx.hpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/matmul_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/matmul_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/matmul_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/matmul_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/max_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/max_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/max_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/max_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/max_pool_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/max_pool_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/max_pool_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/max_pool_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/min_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/min_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/min_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/min_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/pack_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/pack_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/pack_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/pack_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qadd_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qadd_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qadd_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qadd_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qconv2d_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qconv2d_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qconv2d_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qconv2d_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qmatmul_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmatmul_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qmatmul_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmatmul_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qmax_pool_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmax_pool_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qmax_pool_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmax_pool_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qmul_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmul_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qmul_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qmul_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qrelu_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qrelu_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qrelu_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qrelu_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/qreshape_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qreshape_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/qreshape_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/qreshape_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/quantV2_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quantV2_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/quantV2_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quantV2_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/quant_range_for_multiplication_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quant_range_for_multiplication_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/quant_range_for_multiplication_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quant_range_for_multiplication_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quantized_fused_conv2d_maxpool_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/quantized_fused_conv2d_maxpool_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/quantized_fused_conv2d_maxpool_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/relu_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/relu_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/relu_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/relu_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/requant_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/requant_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/requant_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/requant_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/requant_range_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/requant_range_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/requant_range_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/requant_range_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/reshape_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/reshape_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/reshape_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/reshape_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/shape_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/shape_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/shape_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/shape_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/softmax_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/softmax_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/softmax_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/softmax_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/strided_slice_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/strided_slice_op.cpp
similarity index 100%
rename from utensor_cgen/backend/snippets/templates/snippets/strided_slice_op.cpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/strided_slice_op.cpp
diff --git a/utensor_cgen/backend/snippets/templates/snippets/weight_snippet.hpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/weight_snippet.hpp
similarity index 83%
rename from utensor_cgen/backend/snippets/templates/snippets/weight_snippet.hpp
rename to utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/weight_snippet.hpp
index 2ccf15fc..ca098aa2 100644
--- a/utensor_cgen/backend/snippets/templates/snippets/weight_snippet.hpp
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/legacy/weight_snippet.hpp
@@ -1,3 +1 @@
-#include <stdint.h>
-
 const {{ type }} {{ inline_name }} [ {{ length }} ] = { {% for item in value %} {{ item }}, {% endfor %} };
diff --git a/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_op.cpp
new file mode 100644
index 00000000..4fc8112d
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_op.cpp
@@ -0,0 +1,5 @@
+{%if dtypes %}
+{{op_type}}<{%for t in dtypes[:-1]%}{{t}},{%endfor%}{{dtypes[-1]}}> {{op_var_name}};
+{%else%}
+{{op_type}} {{op_var_name}};
+{%endif%}
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_rom_tensor.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_rom_tensor.cpp
new file mode 100644
index 00000000..7aea2018
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/declare_rom_tensor.cpp
@@ -0,0 +1 @@
+Tensor {{tensor_var_name}} = new RomTensor({ {%for s in shape[:-1]%}{{s}}, {%endfor%}{{shape[-1]}} }, {{utensor_dtype}}, {{buffer_var_name}});
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/eval_op.cpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/eval_op.cpp
new file mode 100644
index 00000000..6915a007
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/eval_op.cpp
@@ -0,0 +1,15 @@
+{%for tensor_var, shape in out_shapes_map.items()%}
+Tensor {{tensor_var}} = new RamTensor({ {%for s in shape[:-1]%}{{s}}, {%endfor%}{{shape[-1]}} }, {{out_dtypes_map[tensor_var]}});
+{%endfor%}
+    {{op_name}}
+        .set_inputs({
+{%for name, tensor_var in input_map.items()%}
+            { {{op_type}}::{{name}}, {{tensor_var}} },
+{%endfor%}
+        })
+        .set_outputs({
+{%for name, tensor_var in output_map.items()%}
+            { {{op_type}}::{{name}}, {{tensor_var}}}
+{%endfor%}
+        })
+        .eval();
diff --git a/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/simple.hpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/simple.hpp
new file mode 100644
index 00000000..90e379a8
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/simple.hpp
@@ -0,0 +1,9 @@
+#ifndef __{{model_name.upper()}}_H
+#define __{{model_name.upper()}}_H
+
+#include <vector>
+#include "uTensor/core/tensor.hpp"
+
+void compute_{{model_name}}({%for pl in placeholders%}utensor::Tensor& {{pl}}, {%endfor%}std::vector<utensor::Tensor>& outputs);
+
+#endif // __{{model_name.upper()}}_H
\ No newline at end of file
diff --git a/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/weight.hpp b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/weight.hpp
new file mode 100644
index 00000000..bf9dd673
--- /dev/null
+++ b/utensor_cgen/backend/utensor/snippets/templates/snippets/rearch/weight.hpp
@@ -0,0 +1 @@
+const {{ dtype }} {{ var_name }} [{{ size }}] = { {%for elem in data%} {{elem}}, {%endfor%} };
\ No newline at end of file
diff --git a/utensor_cgen/cli.py b/utensor_cgen/cli.py
index dece5d1a..74cbeead 100644
--- a/utensor_cgen/cli.py
+++ b/utensor_cgen/cli.py
@@ -1,116 +1,106 @@
 #-*- coding:utf8 -*-
+import importlib
 import os
+import re
 import sys
 from pathlib import Path
 
 import click
-import pkg_resources
+from toml import dumps, loads
 
-from utensor_cgen.backend.operators import OperatorFactory
-from utensor_cgen.utils import NArgsKwargsParam, NArgsParam
+from utensor_cgen import __version__
+from utensor_cgen.backend.api import BackendManager
+from utensor_cgen.utils import NArgsParam
 
-_version = (
-  pkg_resources
-  .get_distribution('utensor_cgen')
-  .version
-)
 
 def _get_pb_model_name(path):
   return os.path.basename(os.path.splitext(path)[0])
 
-def _load_transformer(path):
-  # FIXME: better way to activate user plugins other than exec
-  from utensor_cgen.transformer import TransformerPipeline, Transformer
-
-  _globals = {}
-  transform_plugin = Path(path).absolute()
-  with transform_plugin.open('r') as fid:
-    exec(fid.read(), _globals)
-  for obj in _globals.values():
-    if obj is Transformer:
-      continue
-    if isinstance(obj, type) and issubclass(obj, Transformer):
-      TransformerPipeline.register_transformer(obj)
-
+def _load_plugin(path):
+  path = Path(path)
+  if not path.exists():
+    raise RuntimeError('{} does not exists'.format(path))
+  sys.path.insert(0, str(path.parent))
+  mod_name = re.sub(r'.py$', '', path.name.split()[0])
+  importlib.import_module(mod_name)
+  sys.path.pop(0)
 
 @click.group(name='utensor-cli')
 @click.help_option('-h', '--help')
-@click.version_option(_version,
-                       '-V', '--version')
-@click.option("--transform-plugin",
-              default=None,
-              help="path of the python file which user-defined transformers live",
-              metavar="MODULE.py",
+@click.version_option(
+  __version__,
+  '-V', '--version'
 )
-def cli(transform_plugin):
-  if transform_plugin is not None:
-    _load_transformer(transform_plugin)
+@click.option(
+  "-p",
+  "--plugin",
+  multiple=True,
+  help="path of the python module which will be loaded as plugin",
+  metavar="MODULE",
+)
+def cli(plugin):
+  for module in plugin:
+    _load_plugin(module)
+
+@cli.command(name='list-backends', help='list all available backends')
+@click.help_option('-h', '--help')
+def list_backends():
+  click.secho('Available backends:', fg='green', bold=True)
+  for backend in BackendManager.backends:
+    click.secho(
+      '  - {}'.format(backend), fg='green'
+    )
+
+@cli.command(name='generate-config', help='generate config toml file')
+@click.help_option('-h', '--help')
+@click.option('--target', required=True, help='target framework/platform')
+@click.option('-o', '--output', default='utensor_cli.toml', metavar='CONFIG.toml', help='the output config file name')
+def generate_config(target, output):
+  backend_cls = BackendManager.get_backend(target)
+  config = backend_cls.default_config
+  click.secho(
+    'generating config file: {}'.format(output),
+    fg='white',
+    bold=True,
+  )
+  with open(output, 'w') as fid:
+    fid.write(
+      '# https://github.com/toml-lang/toml\n'
+      '# <target_name>.<component>.<part>\n'
+    )
+    fid.write(dumps(config))
 
 @cli.command(name='convert', help='convert graph to cpp/hpp files')
 @click.help_option('-h', '--help')
-@click.argument('pb_file', required=True, metavar='MODEL.pb')
-@click.option('-o', '--output',
-              metavar="FILE.cpp",
-              help="output source file name, header file will be named accordingly. (defaults to protobuf name, e.g.: my_model.cpp)")
-@click.option('-d', '--data-dir',
-              metavar='DIR',
-              help="output directory for tensor data idx files",
-              show_default=True)
-@click.option('-D', '--embed-data-dir',
-              metavar='EMBED_DIR',
-              help=("the data dir on the develop board "
-                    "(default: the value as the value of -d/data-dir flag)"))
-@click.option('--debug-comment',
-              is_flag=True,
-              help="Add debug comments in the output source file",
-              show_default=True)
-@click.option("--output-nodes",
-              type=NArgsParam(),
-              metavar="NODE_NAME,NODE_NAME,...",
-              required=True,
-              help="list of output nodes")
-@click.option("--transform-methods",
-              type=NArgsKwargsParam(sep='|>'),
-              default=(
-                'dropout(name_pattern=r"(dropout[_\w\d]*)/.*")|>linear_reorder'
-                '|>quantize|>conv_pool|>inline|>biasAdd|>remove_id_op'
-                '|>fake_gather_v2|>refcnt'
-              ),
-              help='optimization pipeline',
-              metavar='METHOD[|>METHOD|>...]',
-              show_default=True)
-@click.option("-m", "--model-dir",
-              metavar="DIR",
-              default="models",
-              help="output directory for tensor data idx files",
-              show_default=True)
-@click.option("--save-graph",
-              is_flag=True,
-              help="save transformed graph")
-def convert_graph(pb_file, output, data_dir, embed_data_dir, save_graph,
-                  debug_comment, output_nodes, transform_methods, model_dir):
-  from utensor_cgen.backend import CodeGenerator
-
-  if pb_file is None:
-    raise ValueError("No pb file given")
-
-  if not os.path.exists(model_dir):
-    os.makedirs(model_dir)
-  # MODEL should default to pb_file
-  if data_dir is None:
-    data_dir = os.path.join("constants", _get_pb_model_name(pb_file))
-
-  if output is None:
-    output =  "{}.cpp".format(_get_pb_model_name(pb_file))
-  model_path = os.path.join(model_dir, output)
-
-  if embed_data_dir is None:
-    embed_data_dir = os.path.join("/fs", data_dir)
-  # TODO: pass transformation kwargs to codegenerator (better argument parser)
-  generator = CodeGenerator(pb_file, data_dir, embed_data_dir,
-                            transform_methods, output_nodes,
-                            save_graph, debug_comment)
-  generator.generate(model_path)
+@click.argument(
+  'model_file',
+  required=True,
+  metavar='MODEL_FILE.{pb,onnx,pkl}',
+)
+@click.option(
+  '--output-nodes',
+  type=NArgsParam(),
+  metavar="NODE_NAME,NODE_NAME,...",
+  required=True,
+  help="list of output nodes"
+)
+@click.option('--config', default='utensor_cli.toml', show_default=True, metavar='CONFIG.toml')
+@click.option('--target',
+              default='utensor',
+              show_default=True,
+              help='target framework/platform'
+)
+def convert_graph(model_file, output_nodes, config, target):
+  from utensor_cgen.frontend import FrontendSelector
+
+  if os.path.exists(config):
+    with open(config) as fid:
+      config = loads(fid.read())
+  else:
+    config = {}
+  ugraph = FrontendSelector.parse(model_file, output_nodes, config)
+  backend = BackendManager.get_backend(target)(config)
+  backend.apply(ugraph)
 
 @cli.command(name='list-trans-methods', help='list all available graph transformation')
 @click.help_option('-h', '--help')
@@ -141,27 +131,31 @@ def list_trans_methods(verbose):
               help="list of output nodes")
 @click.argument('model_file', required=True, metavar='MODEL.{pb,pkl}')
 def show_graph(model_file, **kwargs):
+  import pickle
+  from utensor_cgen.frontend import FrontendSelector
   _, ext = os.path.splitext(model_file)
   output_nodes = kwargs.pop('output_nodes')
-  if ext == '.pb' or ext == '.pbtxt':
-    _show_pb_file(model_file, output_nodes=output_nodes, **kwargs)
-  elif ext == '.pkl':
-    import pickle
+
+  if ext == '.pkl':
     with open(model_file, 'rb') as fid:
       ugraph = pickle.load(fid)
     _show_ugraph(ugraph, **kwargs)
-  else:
-    msg = click.style('unknown file extension: {}'.format(ext), fg='red', bold=True)
-    click.echo(msg, file=sys.stderr)
+    return 0
 
-def _show_pb_file(pb_file, output_nodes, **kwargs):
-  import tensorflow as tf
-  from utensor_cgen.frontend.tensorflow import GraphDefParser
-  ugraph = GraphDefParser.parse(pb_file, output_nodes=output_nodes)
-  _show_ugraph(ugraph, **kwargs)
+  try:
+    parser = FrontendSelector.select_parser(ext)
+    ugraph = parser.parse(model_file, output_nodes)
+    _show_ugraph(ugraph, **kwargs)
+    return 0
+  except RuntimeError as err:
+    msg = err.args[0]
+    click.secho(msg, fg='red', bold=True)
+    return 1
 
 def _show_ugraph(ugraph, oneline=False, ignore_unknown_op=False):
   import textwrap
+  from utensor_cgen.backend.utensor.code_generator.legacy._operators import OperatorFactory
+
   unknown_ops = set([])
   if oneline:
     tmpl = click.style("{op_name} ", fg='yellow', bold=True) + \
@@ -200,6 +194,10 @@ def _show_ugraph(ugraph, oneline=False, ignore_unknown_op=False):
       if not OperatorFactory.is_supported(op_info.op_type):
         unknown_ops.add(op_info)
     click.echo('\n'.join(paragraphs))
+  click.secho(
+    'topological ordered ops: {}'.format(ugraph.topo_order),
+    fg='white', bold=True,
+  )
   if unknown_ops and not ignore_unknown_op:
     click.echo(
       click.style('Unknown Ops Detected', fg='red', bold=True)
diff --git a/utensor_cgen/frontend/__init__.py b/utensor_cgen/frontend/__init__.py
index ba0cc7e8..f122ea18 100644
--- a/utensor_cgen/frontend/__init__.py
+++ b/utensor_cgen/frontend/__init__.py
@@ -21,12 +21,20 @@ def _register(parser_cls):
 
     return _register
 
+  @classmethod
+  def parse(cls, model_file, output_nodes, config=None):
+    if config is None:
+      config = {}
+    _, ext = os.path.splitext(model_file)
+    parser = cls.select_parser(ext)(config)
+    return parser.parse(model_file, output_nodes)
+
   @classmethod
   def select_parser(cls, file_ext):
     cls._setup()
     parser_cls = cls._parser_map.get(file_ext, None)
     if parser_cls is None:
-      raise RuntimeError("unknown model file ext found: %s" % file_ext)
+      raise RuntimeError("unknown model file extension: %s" % file_ext)
     return parser_cls
   
   @classmethod
diff --git a/utensor_cgen/frontend/base.py b/utensor_cgen/frontend/base.py
index 6f6ba1ae..86131f65 100644
--- a/utensor_cgen/frontend/base.py
+++ b/utensor_cgen/frontend/base.py
@@ -1,8 +1,16 @@
 from abc import ABCMeta, abstractmethod
 
+
 class Parser(object):
   __metaclass__ = ABCMeta
 
+  def __new__(cls, config):
+    if not isinstance(config, dict):
+      raise ValueError('expecting dict as config, get {}'.format(type(config)))
+    self = object.__new__(cls)
+    self._config = config
+    return self
+
   @classmethod
   @abstractmethod
   def parse(cls, fname, outupt_nodes):
diff --git a/utensor_cgen/frontend/tensorflow.py b/utensor_cgen/frontend/tensorflow.py
index 899838c1..263faa92 100644
--- a/utensor_cgen/frontend/tensorflow.py
+++ b/utensor_cgen/frontend/tensorflow.py
@@ -1,5 +1,7 @@
 from __future__ import absolute_import
 
+import os
+
 import numpy as np
 import six
 
@@ -8,7 +10,8 @@
 from utensor_cgen.frontend import FrontendSelector
 from utensor_cgen.frontend.base import Parser
 from utensor_cgen.ir.base import OperationInfo, TensorInfo, uTensorGraph
-from utensor_cgen.utils import topologic_order_graph
+from utensor_cgen.legalizer import Legalizer
+from utensor_cgen.utils import random_str, topologic_order_graph
 
 
 @FrontendSelector.register(target_exts=['.pb', '.pbtxt'])
@@ -16,7 +19,7 @@ class GraphDefParser(Parser):
 
   @classmethod
   def parse(cls, pb_file, output_nodes=None):
-    graph_def = cls._load_graph_def(pb_file)
+    graph_def, graph_name = cls._load_graph_def(pb_file)
     if not cls._tf_is_freeze_graph(graph_def):
       raise ValueError('Given graph_def is not freezed')
     if output_nodes is None:
@@ -25,9 +28,11 @@ def parse(cls, pb_file, output_nodes=None):
     graph = tf.Graph()
     with graph.as_default():
       tf.import_graph_def(graph_def, name='')
-
-    ugraph = uTensorGraph(output_nodes=output_nodes,
-                          backend="tensorflow")
+    ugraph = uTensorGraph(
+      name=graph_name,
+      output_nodes=output_nodes,
+      lib_name="tensorflow",
+    )
     for node in graph_def.node:
       op = graph.get_operation_by_name(node.name)
       in_tensors = [TensorInfo(name=tensor.name,
@@ -52,19 +57,21 @@ def parse(cls, pb_file, output_nodes=None):
                               output_tensors=out_tensors,
                               n_outputs=len(out_tensors),
                               op_type=op_type,
-                              backend='tensorflow',
+                              lib_name='tensorflow',
                               op_attr=op_attr,
                               ugraph=ugraph)
       op_info.op_attr['tensorflow__device'] = node.device
       ugraph.ops_info[node.name] = op_info
     topologic_order_graph(ugraph)
+    ugraph = Legalizer.legalize(ugraph, {})
     return ugraph
 
   @staticmethod
   def _load_graph_def(pb_file):
     if isinstance(pb_file, tf.GraphDef):
-      return pb_file
+      return pb_file, 'tf_graph_{}'.format(random_str(6))
     assert isinstance(pb_file, six.string_types)
+    graph_name, _ = os.path.splitext(os.path.basename(pb_file))
     graph_def = tf.GraphDef()
     if pb_file[-3:] == ".pb":
       with open(pb_file, 'rb') as fid:
@@ -74,8 +81,7 @@ def _load_graph_def(pb_file):
         text_format.Parse(fid.read(), graph_def)
     else:
       raise ValueError('unknown file format: %s' % pb_file)
-    return graph_def
-
+    return graph_def, graph_name
 
   @staticmethod
   def _tf_parse_tshape(t_shape):
diff --git a/utensor_cgen/ir/base.py b/utensor_cgen/ir/base.py
index 538a7d4e..d1137786 100644
--- a/utensor_cgen/ir/base.py
+++ b/utensor_cgen/ir/base.py
@@ -4,10 +4,10 @@
 from functools import reduce
 
 import attr
-import numpy as np
 import six
 from attr.validators import instance_of
 
+import numpy as np
 import tensorflow as tf
 from tensorflow.core.framework.attr_value_pb2 import AttrValue as _AttrValue
 from tensorflow.core.framework.attr_value_pb2 import \
@@ -38,7 +38,7 @@ def __copy__(self):
 class IRBase(object):
 
   @property
-  def all_supported_backends(self):
+  def all_supported_libs(self):
     return ['tensorflow']
 
 
@@ -69,20 +69,21 @@ class TensorInfo(IRBase, _NoShallowCopyMixin):
   dtype = attr.ib(validator=instance_of(np.dtype))
 
   shape = attr.ib(validator=instance_of((list, type(None))))
-  
   @shape.validator
   def check(self, attrib, shape_values):
     if shape_values is not None:
       for v in shape_values:
         assert isinstance(v, (int, type(None))), \
           "shape should be a list of integers"
-          
+
   _ugraph = attr.ib(repr=False)
   @_ugraph.validator
   def check(self, attrib, value):
     if not isinstance(value, uTensorGraph):
       raise ValueError('Expecting a uTensorGraph, get {}'.format(type(value)))
 
+  attributes = attr.ib(factory=dict, validator=instance_of(dict))
+
   _NULL_PREFIX = 'utensor_null'
 
   def move_into(self, ugraph):
@@ -153,14 +154,14 @@ def op(self):
     return op
 
   @property
-  def backend(self):
+  def lib_name(self):
     """
-    the name of backend library/framework used for training
+    the name of training library/framework
     the graph
 
     :rtype: six.string_types
     """
-    return self._ugraph.backend
+    return self._ugraph._lib_name
   
   @property
   def is_null_tensor(self):
@@ -189,7 +190,13 @@ def __hash__(self):
   def __eq__(self, other):
     if not isinstance(other, type(self)):
       return False
-    return (self.name == other.name) and (self._ugraph is other._ugraph)
+    return (
+      (self.name == other.name) and
+      (self._ugraph is other._ugraph) and
+      (self.op_name == other.op_name) and
+      (self.dtype == other.dtype) and
+      (self.shape == other.shape)
+    )
 
 
 @attr.s(cmp=False, repr=False)
@@ -207,9 +214,8 @@ class OperationInfo(IRBase, _NoShallowCopyMixin):
   :param op_type: the type of the node (ex: ``Add``)
   :type op_type: str
 
-  :param backend: the name of the backend, the library/framework for the training phase
-    {'tensorflow', 'pytorch'}
-  :type backend: str
+  :param lib_name: the name of the training library/framework, {'tensorflow', 'pytorch'}
+  :type lib_name: str
 
   :param ugraph: the graph which owns this op
   :type ugraph: :py:class:`.uTensorGraph`
@@ -226,7 +232,7 @@ class OperationInfo(IRBase, _NoShallowCopyMixin):
     - The values of such keys will be saved **as-is** without any type conversion.
   """
   name = attr.ib(type=str)
-  _backend = attr.ib(type=str)
+  _lib_name = attr.ib(type=str)
   _ugraph = attr.ib(repr=False)
   @_ugraph.validator
   def check(self, attrib, value):
@@ -295,13 +301,13 @@ def ugraph(self):
     return self._ugraph
   
   @property
-  def backend(self):
+  def lib_name(self):
     """
-    The name of backend library/framework
+    The name of training library/framework
 
     :rtype: six.strings_type
     """
-    return self._backend
+    return self._lib_name
 
   @property
   def input_nodes(self):
@@ -390,7 +396,7 @@ def __deepcopy__(self, memo):
                             output_tensors=deepcopy(self.output_tensors, memo),
                             n_outputs=self.n_outputs,
                             op_type=self.op_type,
-                            backend=self.backend,
+                            lib_name=self.lib_name,
                             op_attr=deepcopy(self.op_attr, memo),
                             ugraph=memo['ugraph'])
     return op_info
@@ -424,10 +430,9 @@ class uTensorGraph(IRBase, _NoShallowCopyMixin, uTensorGraphBuilderMixin):
   :param ops_info: a dict with key as string, the op's name,
     and value as an instance of :class:`.OperationInfo`
   :type ops_info: dict
-  :param backend: the name of backend library/framework
-    the graph trained with. Can only be ``'tensorflow'``
-    or ``'pytorch'`` (future work)
-  :type backend: str
+  :param lib_name: the name of library/framework training the graph. 
+  Can only be ``'tensorflow'`` or ``'pytorch'`` (future work)
+  :type lib_name: str
 
   ..
 
@@ -441,7 +446,7 @@ class uTensorGraph(IRBase, _NoShallowCopyMixin, uTensorGraphBuilderMixin):
       1. create a empty graph
 
         - give a list of names of output nodes (required)
-        - (optional) give backend string
+        - (optional) give `lib_name` string
         - leave **ops_info** empty
       2. setup the **ops_info**
 
@@ -452,8 +457,9 @@ class uTensorGraph(IRBase, _NoShallowCopyMixin, uTensorGraphBuilderMixin):
   """
   KWPARSER_PATTERN = re.compile(r'^([^\d\W][\w\d_]*)__([^\d\W][\w\d_]*)')
 
+  name = attr.ib(default='model_graph')
   output_nodes = attr.ib(factory=list)
-  _backend = attr.ib(default='tensorflow', type=six.string_types)
+  _lib_name = attr.ib(default='tensorflow', type=six.string_types)
   ops_info = attr.ib(factory=dict)
   # non-init
   topo_order = attr.ib(factory=list, init=False)
@@ -468,6 +474,7 @@ def __attrs_post_init__(self):
       raise ValueError(
         'output_nodes should be list of str: {}'.format(self.output_nodes)
       )
+    self.name = self.name.replace('/', '_')
   
   def get_ops_by_type(self, given_op_type):
     """
@@ -556,13 +563,13 @@ def input_tensors(self):
     return in_tensors
   
   @property
-  def backend(self):
+  def lib_name(self):
     """
-    the name of backend library/framework
+    the name of training library/framework
 
     :rtype: six.strings_type
     """
-    return self._backend
+    return self._lib_name
 
   @property
   def graph_def(self):
@@ -573,8 +580,8 @@ def graph_def(self):
     """
     if self.output_nodes and not self.topo_order:
       raise RuntimeError('the graph is not topological sorted')
-    assert self._backend == 'tensorflow', \
-      'Convert a uTensorGraph to tf.GraphDef from a non-tf backend'
+    assert self._lib_name == 'tensorflow', \
+      'Can not convert a uTensorGraph to tf.GraphDef from a non-tf graph'
     graph_def = tf.GraphDef()
     for node_name in self.topo_order:
       op_info = self.ops_info[node_name]
@@ -652,8 +659,9 @@ def unsafe_merge_into(self, other_ugraph):
 
   def __deepcopy__(self, memo):
     new_graph = uTensorGraph(
+      name=self.name,
       output_nodes=self.output_nodes,
-      backend=self._backend
+      lib_name=self._lib_name
     )
     memo['ugraph'] = new_graph
     new_graph.ops_info = {
@@ -663,7 +671,7 @@ def __deepcopy__(self, memo):
     if self.data_manager:
       new_graph.data_manager = DataManager({})
       new_graph.data_manager.StorageCenter = deepcopy(self.data_manager.StorageCenter)
-    new_graph._backend = self._backend
+    new_graph._lib_name = self._lib_name
     topologic_order_graph(new_graph)
     return new_graph
 
@@ -686,8 +694,8 @@ def __attrs_post_init__(self):
       self.ops_info[name] = self._ugraph.ops_info[name]
   
   @property
-  def backend(self):
-    return self._ugraph.backend
+  def lib_name(self):
+    return self._ugraph._lib_name
 
   @property
   def input_ops(self):
diff --git a/utensor_cgen/ir/graph_builder.py b/utensor_cgen/ir/graph_builder.py
index 83dc04ff..17c5d3b4 100644
--- a/utensor_cgen/ir/graph_builder.py
+++ b/utensor_cgen/ir/graph_builder.py
@@ -3,7 +3,7 @@
 
 from utensor_cgen.utils import LazyLoader, topologic_order_graph
 
-operators = LazyLoader('backend.operators')
+operators = LazyLoader(submod_name='backend.utensor.code_generator.legacy._operators')
 
 
 class GraphFinalizedError(Exception): pass
diff --git a/utensor_cgen/legalizer/__init__.py b/utensor_cgen/legalizer/__init__.py
new file mode 100644
index 00000000..15e82b78
--- /dev/null
+++ b/utensor_cgen/legalizer/__init__.py
@@ -0,0 +1,34 @@
+from .base import LegalizerBase
+from .tensorflow import GraphDefLegalizer
+
+
+class Legalizer(object):
+  LEGALIZER_MAP = {}
+
+  @classmethod
+  def register(cls, legalizer=None):
+    def _register(legalizer_):
+      if not issubclass(legalizer_, LegalizerBase):
+        raise TypeError(
+          'expecting subclass of {}, get {}'.format(LegalizerBase, legalizer_)
+        )
+      cls.LEGALIZER_MAP[legalizer_.TARGET] = legalizer_
+      return legalizer_
+    if legalizer is None:
+      return _register
+    else:
+      return _register(legalizer)
+  
+  @classmethod
+  def legalize(cls, ugraph, config=None):
+    if config is None:
+      config = {}
+    legalizer_cls = cls.LEGALIZER_MAP.get(ugraph.lib_name)
+    if legalizer_cls is None:
+      raise ValueError(
+        'graph of unsupported lib given: {}'.format(ugraph.lib_name)
+      )
+    legalizer = legalizer_cls(config)
+    return legalizer.legalize(ugraph)
+
+Legalizer.register(GraphDefLegalizer)
diff --git a/utensor_cgen/legalizer/base.py b/utensor_cgen/legalizer/base.py
new file mode 100644
index 00000000..e401eb8b
--- /dev/null
+++ b/utensor_cgen/legalizer/base.py
@@ -0,0 +1,29 @@
+from utensor_cgen.utils import MUST_OVERWRITEN
+
+
+class LegalizerBase(object):
+
+  TARGET = MUST_OVERWRITEN
+  COMPONET = 'legalizer'
+
+  def __new__(cls, config):
+    if not isinstance(config, dict):
+      raise TypeError(
+        'expecting dict as config, get {}'.format(type(config))
+      )
+    if cls.TARGET is MUST_OVERWRITEN:
+      raise ValueError('cls.TARGET must be overwriten')
+    self = object.__new__(cls)
+    self._config = config
+    return self
+
+  def legalize(self, ugraph):
+    ugraph = self.legalize_ops(ugraph)
+    ugraph = self.legalize_dtype(ugraph)
+    return ugraph
+
+  def legalize_ops(self, ugraph):
+    raise NotImplementedError('abstract ops legalizer get called')
+
+  def legalize_dtype(self, ugraph):
+    raise NotImplementedError('abstract dtype legalizer get called')
diff --git a/utensor_cgen/legalizer/tensorflow.py b/utensor_cgen/legalizer/tensorflow.py
new file mode 100644
index 00000000..e2850c68
--- /dev/null
+++ b/utensor_cgen/legalizer/tensorflow.py
@@ -0,0 +1,23 @@
+from .base import LegalizerBase
+
+
+class GraphDefLegalizer(LegalizerBase):
+  TARGET = 'tensorflow'
+
+  def legalize_ops(self, ugraph):
+    '''Legalize ops to generic ops in given graph
+    '''
+    if not ugraph.lib_name == self.TARGET:
+      raise ValueError(
+        'expecting tensorflow graph, get {}'.format(ugraph.lib_name)
+      )
+    return ugraph
+
+  def legalize_dtype(self, ugraph):
+    '''Legalize data types of tensors in given graph
+    '''
+    if not ugraph.lib_name == self.TARGET:
+      raise ValueError(
+        'expecting tensorflow graph, get {}'.format(ugraph.lib_name)
+      )
+    return ugraph
diff --git a/utensor_cgen/matcher/_matcher_impl.py b/utensor_cgen/matcher/_matcher_impl.py
index a2bacb2a..4eca39e8 100644
--- a/utensor_cgen/matcher/_matcher_impl.py
+++ b/utensor_cgen/matcher/_matcher_impl.py
@@ -73,9 +73,7 @@ def query(cls, sub_op, patrn_op):
     equivalent_ops : List[OperationInfo]
       a list of equivalent ops derieved from `sub_op`
     """
-    # to activate all configurations
-    import utensor_cgen.backend.operators as _
-
+    cls._setup()
     is_eq = False
     equivalent_ops = []
     if sub_op is None or patrn_op is None:
@@ -91,7 +89,7 @@ def query(cls, sub_op, patrn_op):
         equivalent_ops.append(
           OperationInfo(
             name=sub_op.name,
-            backend=sub_op.backend,
+            lib_name=sub_op.lib_name,
             ugraph=sub_op.ugraph,
             input_tensors=[sub_op.input_tensors[j] for j in perm],
             n_inputs=sub_op.n_inputs,
@@ -107,7 +105,11 @@ def query(cls, sub_op, patrn_op):
       equivalent_ops = [MetaOperationInfo(op_info=sub_op, morphism=morphism)]
 
     return is_eq, equivalent_ops
-
+  
+  @classmethod
+  def _setup(cls):
+    # to activate all configurations
+    import utensor_cgen.backend.utensor.code_generator.legacy._operators
 
 @attr.s
 class uTensorGraphMatcher(object):
diff --git a/utensor_cgen/transformer/conv_pool.py b/utensor_cgen/transformer/conv_pool.py
index c4950a1d..21cae4e0 100644
--- a/utensor_cgen/transformer/conv_pool.py
+++ b/utensor_cgen/transformer/conv_pool.py
@@ -58,8 +58,9 @@ def transform(self, ugraph):
   def __call__(self, match):
     op_name = 'quant_conv_pool'
     repl_ugraph = uTensorGraph(
+      name='{}_repl_graph'.format(op_name),
       output_nodes=[op_name],
-      backend=match.subject_ugraph.backend
+      lib_name=match.subject_ugraph.lib_name
     )
     subj_conv_op = match.patrn2subj_op_map['conv/eightbit']
     subj_pool_op = match.patrn2subj_op_map['maxpool/eightbit']
@@ -84,7 +85,7 @@ def __call__(self, match):
       output_tensors=output_tensors,
       n_outputs=len(output_tensors),
       op_type='QuantizedFusedConv2DMaxpool',
-      backend=subj_conv_op.backend,
+      lib_name=subj_conv_op.lib_name,
       op_attr={
         '_utensor_conv': subj_conv_op.op_attr,
         '_utensor_pool': subj_pool_op.op_attr,
diff --git a/utensor_cgen/transformer/ns_transformer.py b/utensor_cgen/transformer/ns_transformer.py
index e6c66869..f4fdee2d 100644
--- a/utensor_cgen/transformer/ns_transformer.py
+++ b/utensor_cgen/transformer/ns_transformer.py
@@ -269,7 +269,7 @@ def __init__(self, name_pattern=r'(dropout[_\w\d]*)/.*'):
     self._op_name_pattern = re.compile(name_pattern)
 
   def transform(self, ugraph):
-    new_graph = uTensorGraph(output_nodes=ugraph.output_nodes)
+    new_graph = uTensorGraph(name=ugraph.name, output_nodes=ugraph.output_nodes)
     dropout_input_map = self._find_input(ugraph)
     new_ops_info = {}
     for node_name in ugraph.ops_info:
@@ -299,12 +299,12 @@ def transform(self, ugraph):
                                   output_tensors=out_t_infos,
                                   n_outputs=len(out_t_infos),
                                   op_type=op_info.op_type,
-                                  backend=op_info.backend,
+                                  lib_name=op_info.lib_name,
                                   op_attr=op_attr,
                                   ugraph=new_graph)
       new_ops_info[node_name] = new_op_info
     new_graph.ops_info = new_ops_info
-    new_graph._backend = ugraph._backend
+    new_graph._lib_name = ugraph._lib_name
     return new_graph
 
   def _find_dropout_clusters(self, ugraph):
@@ -380,11 +380,11 @@ def pattern_ugraph(self):
   
   def transform(self, ugraph):
     new_ugraph = deepcopy(ugraph)
-    if new_ugraph.backend == 'tensorflow':
+    if new_ugraph.lib_name == 'tensorflow':
       new_ugraph = self._transform_tf(new_ugraph)
     else:
       raise ValueError(
-        'only support dropout transformer for tensorflow: get {}'.format(new_ugraph.backend)
+        'dropout transformer only support tensorflow graph, get {}'.format(new_ugraph.lib_name)
       )
     return new_ugraph
   
diff --git a/utensor_cgen/transformer/optimizer.py b/utensor_cgen/transformer/optimizer.py
index 89d96c59..e83d081c 100644
--- a/utensor_cgen/transformer/optimizer.py
+++ b/utensor_cgen/transformer/optimizer.py
@@ -54,10 +54,10 @@ def __init__(self, **kwargs):
     self.prune_graph = True
 
   def transform(self, ugraph):
-    if ugraph.backend == 'tensorflow':
+    if ugraph.lib_name == 'tensorflow':
       return self._transform_tf(ugraph)
     else:
-      raise RuntimeError('unsupported backend: {}'.format(ugraph.backend))
+      raise RuntimeError('unsupported lib_name: {}'.format(ugraph.lib_name))
 
   def _transform_tf(self, ugraph):
     ops_to_remove = [
diff --git a/utensor_cgen/transformer/pipeline.py b/utensor_cgen/transformer/pipeline.py
index da4fe2fb..500f58a0 100644
--- a/utensor_cgen/transformer/pipeline.py
+++ b/utensor_cgen/transformer/pipeline.py
@@ -1,3 +1,6 @@
+import re
+from ast import literal_eval
+
 from .base import Transformer
 
 
@@ -5,16 +8,25 @@ class TransformerPipeline(object):
 
   TRANSFORMER_MAP = {}
 
+  _trans_name_patrn = re.compile(r"(\w[\w]*)\(?")
+
   def __init__(self, methods):
     """
     methods : list
-      list of tuples, (transform_name, kwargs)
+      list of tuples of type Tuple[Type[Transformer], dict] or a string expression
+      of the transformer such as 'dropout(name_pattern=r"(dropout[_\w\d]*)/.*")'
     """
     self._pipeline = []
-    for method, kwargs in methods:
-      trans_cls = self.TRANSFORMER_MAP.get(method, None)
-      if trans_cls is None:
-        raise ValueError("Unknown transformation method: {}".format(method))
+    for method_or_str in methods:
+      if isinstance(method_or_str, str):
+        method, kwargs = self._parse_expr(method_or_str)
+        trans_cls = self.TRANSFORMER_MAP.get(method, None)
+        if trans_cls is None:
+          raise ValueError("Unknown transformation method: {}".format(method))
+      else:
+        trans_cls, kwargs = method_or_str
+      if not issubclass(trans_cls, Transformer):
+        raise TypeError("expecting subclass of {}, get {}".format(Transformer, trans_cls))
       transformer = trans_cls(**kwargs)
       self._pipeline.append(transformer)
   
@@ -44,3 +56,28 @@ def register(trans_cls):
     if trans_cls is None:
       return register
     return register(trans_cls)
+  
+  @classmethod
+  def _parse_expr(cls, expr):
+    trans_match = cls._trans_name_patrn.match(expr)
+    if not trans_match:
+      raise ValueError("Invalid args detected: {}".format(expr))
+    trans_name = trans_match.group(1)
+    _, end = trans_match.span()
+    if end == len(expr):
+      kwargs = {}
+    else:
+      if not expr.endswith(")"):
+        raise ValueError("parentheses mismatch: {}".format(expr))
+      kwargs = cls._get_kwargs(expr[end:-1])
+    return trans_name, kwargs
+
+  @classmethod
+  def _get_kwargs(cls, kws_str):
+    kw_arg_strs = [s.strip() for s in kws_str.split(',')]
+    kwargs = {}
+    for kw_str in kw_arg_strs:
+      name, v_str = kw_str.split('=')
+      value = literal_eval(v_str)
+      kwargs[name] = value
+    return kwargs
diff --git a/utensor_cgen/transformer/quantize.py b/utensor_cgen/transformer/quantize.py
index 1fdf9ecc..d876ed69 100644
--- a/utensor_cgen/transformer/quantize.py
+++ b/utensor_cgen/transformer/quantize.py
@@ -13,7 +13,6 @@ class QuantizeTransformer(Transformer):
   KWARGS_NAMESCOPE = '_quantize'
 
   def transform(self, ugraph):
-    #import pdb; pdb.set_trace()
     graph_def = ugraph.graph_def
     quant_graph_def = TransformGraph(input_graph_def=graph_def,
                                      inputs=[],
diff --git a/utensor_cgen/utils.py b/utensor_cgen/utils.py
index 28fea2a7..006bf0dd 100644
--- a/utensor_cgen/utils.py
+++ b/utensor_cgen/utils.py
@@ -9,18 +9,59 @@
 from random import choice
 from string import ascii_letters, digits
 
+import attr
 import numpy as np
 from click.types import ParamType
+from toml import loads as _parse
 
 import idx2numpy as idx2np
-import tensorflow as tf
-from tensorflow.python.framework import graph_util
-from tensorflow.tools.graph_transforms import TransformGraph
 from utensor_cgen.logger import logger
 
 __all__ = ["save_idx", "save_consts", "save_graph", "log_graph",
            "NamescopedKWArgsParser", "NArgsParam", "MUST_OVERWRITEN"]
 
+class LazyLoader(types.ModuleType):
+
+  def __init__(self, module_name='utensor_cgen', submod_name=None):
+    self._module_name = '{}{}'.format(
+      module_name,
+      submod_name and '.{}'.format(submod_name) or ''
+    )
+    self._mod = None
+    super(LazyLoader, self).__init__(self._module_name)
+
+  def _load(self):
+    if self._mod is None:
+      self._mod = importlib.import_module(
+        self._module_name
+      )
+    return self._mod
+
+  def __getattr__(self, attrb):
+    return getattr(self._load(), attrb)
+
+  def __dir__(self):
+    return dir(self._load())
+
+tf = LazyLoader('tensorflow')
+tf_python = LazyLoader('tensorflow', 'python.framework')
+
+class LazyAttrib(object):
+
+  def __init__(self, obj, attr_name):
+    self._obj = obj
+    self._attr_name = attr_name
+
+  def __getattr__(self, name):
+    return getattr(self.attrib, name)
+  
+  def __call__(self, *args, **kwargs):
+    return self.attrib(*args, **kwargs)
+
+  @property
+  def attrib(self):
+    return getattr(self._obj, self._attr_name)
+
 
 def log_graph(graph_or_graph_def, logdir):
   if isinstance(graph_or_graph_def, tf.GraphDef):
@@ -96,8 +137,8 @@ def prepare_meta_graph(meta_graph_path, output_nodes, chkp_path=None):
     chkp_path = meta_graph_path.replace(".meta", "")
   with tf.Session(graph=graph) as sess:
     saver.restore(sess, chkp_path)
-    graph_def = graph_util.remove_training_nodes(sess.graph_def)
-    sub_graph_def = graph_util.convert_variables_to_constants(sess=sess,
+    graph_def = tf_python.graph_util.remove_training_nodes(sess.graph_def)
+    sub_graph_def = tf_python.graph_util.convert_variables_to_constants(sess=sess,
                                                               input_graph_def=graph_def,
                                                               output_node_names=output_nodes)
   return sub_graph_def
@@ -273,38 +314,6 @@ def convert(self, value, param, ctx):
     return final_args
 
 
-class NArgsKwargsParam(NArgsParam):
-
-  _trans_name_patrn = re.compile(r"(\w[\w]*)\(?")
-
-  def convert(self, value, param, ctx):
-    args = super(NArgsKwargsParam, self).convert(value, param, ctx)
-    return [self._parse_kwargs(arg) for arg in args]
-  
-  def _parse_kwargs(self, arg):
-    trans_match = self._trans_name_patrn.match(arg)
-    if not trans_match:
-      raise ValueError("Invalid args detected: {}".format(arg))
-    trans_name = trans_match.group(1)
-    _, end = trans_match.span()
-    if end == len(arg):
-      kwargs = {}
-    else:
-      if not arg.endswith(")"):
-        raise ValueError("parentheses mismatch: {}".format(arg))
-      kwargs = self._get_kwargs(arg[end:-1])
-    return trans_name, kwargs
-  
-  def _get_kwargs(self, kws_str):
-    kw_arg_strs = [s.strip() for s in kws_str.split(',')]
-    kwargs = {}
-    for kw_str in kw_arg_strs:
-      name, v_str = kw_str.split('=')
-      value = literal_eval(v_str)
-      kwargs[name] = value
-    return kwargs
-
-
 class _MustOverwrite(object):
   _obj = None
 
@@ -313,6 +322,7 @@ def __new__(cls, *args, **kwargs):
       cls._obj = object.__new__(cls, *args, **kwargs)
     return cls._obj
 
+
 MUST_OVERWRITEN = _MustOverwrite()
 
 
@@ -342,7 +352,7 @@ def get_topologic_order(ugraph, init_nodes=None):
 
   - `Topological Sorting (wiki) <https://en.wikipedia.org/wiki/Topological_sorting>`_
   """
-  if ugraph.backend != "tensorflow":
+  if ugraph.lib_name != "tensorflow":
     raise ValueError(
       "topologic_order_graph works only on tensorflow graph"
     )
@@ -450,20 +460,86 @@ def random_str(length=8):
   return ''.join(chars)
 
 
-class LazyLoader(types.ModuleType):
+class class_property(object):
+    
+  def __init__(self, getter):
+    self._getter = getter
+      
+  def __get__(self, obj, objtype=None):
+    if objtype is None:
+      return self._getter(obj)
+    return self._getter(objtype)
 
-  def __init__(self, submod_name):
-    self._submod_name = submod_name
-    self._submod = None
-    super(LazyLoader, self).__init__(submod_name)
 
-  def _load(self):
-    if self._submod is None:
-      self._submod = importlib.import_module('utensor_cgen.{}'.format(self._submod_name))
-    return self._submod
+@attr.s
+class Pipeline(object):
+  _funcs = attr.ib(factory=list)
 
-  def __getattr__(self, attrb):
-    return getattr(self._load(), attrb)
+  def __call__(self, *args, **kwargs):
+    result = None
+    for func in self._funcs:
+      if result is None:
+        result = func(*args, **kwargs)
+      else:
+        result = func(*result)
+    return result
+
+  def __getitem__(self, slice_obj):
+    cls = type(self)
+    return cls(funcs=self._funcs[slice_obj])
+
+
+def parse_toml(file_or_path):
+  if isinstance(file_or_path, str):
+    fid = open(file_or_path, 'r')
+  doc = _parse(fid.read())
+  fid.close()
+  return doc
+
+
+class Configuration(object):
+  def __init__(self, defaults=None, user_config=None):
+    if defaults is None:
+      defaults = {}
+    if user_config is None:
+      user_config = {}
+    self._defaults = defaults
+    self._user_config = user_config
+
+  @property
+  def defaults(self):
+    return self._defaults
+  
+  @property
+  def user_config(self):
+    return self._user_config
+  
+  def get(self, key, default=None):
+    value = default
+    if key in self._user_config:
+      value = self._user_config[key]
+    elif key in self._defaults:
+      value = self._defaults[key]
+    return value
+     
+
+  def __getitem__(self, key):
+    if key not in self:
+      raise KeyError('invalid key: {}'.format(key))
+    value = self._user_config.get(
+      key, self._defaults[key]
+    )
+    if isinstance(value, dict):
+      value = type(self)(value, {})
+    return value
 
-  def __dir__(self):
-    return dir(self._load())
+  def __contains__(self, key):
+    return key in self._user_config or key in self._defaults
+
+  def __repr__(self):
+    return (
+      'Configuration(\n'
+      '  defaults={},\n'
+      '  user_config={} \n'
+      ')'
+    ).format(self._defaults, self._user_config)