ExtractSeqLensJob

returnn/dataset.py

@@ -5,7 +5,7 @@
 import pickle
 import shutil
 import subprocess
-from typing import Optional
+from typing import Optional, Any, Dict
 
 import numpy
 
@@ -149,3 +149,110 @@ def run(self):
                 hdf_writer.insert_batch(numpy.asarray([[speaker_index]], dtype="int32"), [1], [segment_name])
 
         hdf_writer.close()
+
+
+class ExtractSeqLensJob(Job):
+    """
+    Extracts sequence lengths from a dataset for one specific key.
+
+    Also see: :class:`i6_experiments.users.schmitt.corpus.statistics.GetSeqLenFileJob`
+    """
+
+    # noinspection PyShadowingBuiltins
+    def __init__(
+        self,
+        dataset: Dict[str, Any],
+        post_dataset: Optional[Dict[str, Any]] = None,
+        *,
+        key: str,
+        format: str,
+        returnn_config: Optional[ReturnnConfig] = None,
+    ):
+        """
+        :param dataset: dict for :func:`returnn.datasets.init_dataset`
+        :param post_dataset: extension of the dataset dict, which is not hashed
+        :param key: e.g. "data", "classes" or whatever the dataset provides
+        :param format: "py" or "txt"
+        :param returnn_config: for the RETURNN global config.
+            This is optional and only needed if you use any custom functions (e.g. audio pre_process)
+            which expect some configuration in the global config.
+        """
+        super().__init__()
+        self.dataset = dataset
+        self.post_dataset = post_dataset
+        self.key = key
+        assert format in {"py", "txt"}
+        self.format = format
+        self.returnn_config = returnn_config
+
+        self.out_returnn_config_file = self.output_path("returnn.config")
+        self.out_file = self.output_path(f"seq_lens.{format}")
+
+        self.rqmt = {"gpu": 0, "cpu": 1, "mem": 4, "time": 1}
+
+    @classmethod
+    def hash(cls, parsed_args):
+        """hash"""
+        parsed_args = parsed_args.copy()
+        parsed_args.pop("post_dataset")
+        if not parsed_args["returnn_config"]:
+            parsed_args.pop("returnn_config")
+        return super().hash(parsed_args)
+
+    def tasks(self):
+        """tasks"""
+        yield Task("create_files", mini_task=True)
+        yield Task("run", rqmt=self.rqmt)
+
+    def create_files(self):
+        """create files"""
+        config = self.returnn_config or ReturnnConfig({})
+        assert "dataset" not in config.config and "dataset" not in config.post_config
+        dataset_dict = self.dataset.copy()
+        if self.post_dataset:
+            # The modification to the config here is not part of the hash anymore,
+            # so merge dataset and post_dataset now.
+            dataset_dict.update(self.post_dataset)
+        config.config["dataset"] = dataset_dict
+        config.write(self.out_returnn_config_file.get_path())
+
+    def run(self):
+        """run"""
+        import tempfile
+        import shutil
+        from returnn.config import set_global_config, Config
+        from returnn.datasets import init_dataset
+
+        config = Config()
+        config.load_file(self.out_returnn_config_file.get_path())
+        set_global_config(config)
+
+        dataset_dict = config.typed_value("dataset")
+        assert isinstance(dataset_dict, dict)
+        dataset = init_dataset(dataset_dict)
+        dataset.init_seq_order(epoch=1)
+
+        with tempfile.NamedTemporaryFile("w") as tmp_file:
+            if self.format == "py":
+                tmp_file.write("{\n")
+
+            seq_idx = 0
+            while dataset.is_less_than_num_seqs(seq_idx):
+                dataset.load_seqs(seq_idx, seq_idx + 1)
+                seq_tag = dataset.get_tag(seq_idx)
+                seq_len = dataset.get_seq_length(seq_idx)
+                assert self.key in seq_len.keys()
+                seq_len_ = seq_len[self.key]
+                if self.format == "py":
+                    tmp_file.write(f"{seq_tag!r}: {seq_len_},\n")
+                elif self.format == "txt":
+                    tmp_file.write(f"{seq_len_}\n")
+                else:
+                    raise ValueError(f"{self}: invalid format {self.format!r}")
+                seq_idx += 1
+
+            if self.format == "py":
+                tmp_file.write("}\n")
+            tmp_file.flush()
+
+            shutil.copyfile(tmp_file.name, self.out_file.get_path())