Refactor Frame and FrameBatch into their own source file

docs/source/api_ref_decoders.rst

@@ -20,6 +20,4 @@ torchcodec.decoders
     :nosignatures:
     :template: dataclass.rst
 
-    Frame
-    FrameBatch
     VideoStreamMetadata

docs/source/api_ref_torchcodec.rst

@@ -0,0 +1,16 @@
+.. _torchcodec:
+
+===================
+torchcodec
+===================
+
+.. currentmodule:: torchcodec
+
+
+.. autosummary::
+    :toctree: generated/
+    :nosignatures:
+    :template: dataclass.rst
+
+    Frame
+    FrameBatch

docs/source/index.rst

@@ -45,7 +45,7 @@ We achieve these capabilities through:
      .. grid-item-card:: :octicon:`file-code;1em`
         API Reference
         :img-top: _static/img/card-background.svg
-        :link: api_ref_decoders.html
+        :link: api_ref_torchcodec.html
         :link-type: url
 
         The API reference for TorchCodec
@@ -73,4 +73,5 @@ We achieve these capabilities through:
    :caption: API Reference
    :hidden:
 
+   api_ref_torchcodec
    api_ref_decoders

examples/basic_example.py

@@ -121,8 +121,8 @@ def plot(frames: torch.Tensor, title : Optional[str] = None):
 # This can be achieved using the
 # :meth:`~torchcodec.decoders.VideoDecoder.get_frame_at` and
 # :meth:`~torchcodec.decoders.VideoDecoder.get_frames_at`  methods, which
-# will return a :class:`~torchcodec.decoders.Frame` and
-# :class:`~torchcodec.decoders.FrameBatch` objects respectively.
+# will return a :class:`~torchcodec.Frame` and
+# :class:`~torchcodec.FrameBatch` objects respectively.
 
 last_frame = decoder.get_frame_at(len(decoder) - 1)
 print(f"{type(last_frame) = }")
@@ -138,12 +138,12 @@ def plot(frames: torch.Tensor, title : Optional[str] = None):
 plot(middle_frames.data, "Middle frames")
 
 # %%
-# Both :class:`~torchcodec.decoders.Frame` and
-# :class:`~torchcodec.decoders.FrameBatch` have a ``data`` field, which contains
+# Both :class:`~torchcodec.Frame` and
+# :class:`~torchcodec.FrameBatch` have a ``data`` field, which contains
 # the decoded tensor data. They also have the ``pts_seconds`` and
 # ``duration_seconds`` fields which are single ints for
-# :class:`~torchcodec.decoders.Frame`, and 1-D :class:`torch.Tensor` for
-# :class:`~torchcodec.decoders.FrameBatch` (one value per frame in the batch).
+# :class:`~torchcodec.Frame`, and 1-D :class:`torch.Tensor` for
+# :class:`~torchcodec.FrameBatch` (one value per frame in the batch).
 
 # %%
 # Using time-based indexing
@@ -153,7 +153,7 @@ def plot(frames: torch.Tensor, title : Optional[str] = None):
 # frames based on *when* they are displayed with
 # :meth:`~torchcodec.decoders.VideoDecoder.get_frame_displayed_at` and
 # :meth:`~torchcodec.decoders.VideoDecoder.get_frames_displayed_at`, which
-# also returns :class:`~torchcodec.decoders.Frame` and :class:`~torchcodec.decoders.FrameBatch`
+# also returns :class:`~torchcodec.Frame` and :class:`~torchcodec.FrameBatch`
 # respectively.
 
 frame_at_2_seconds = decoder.get_frame_displayed_at(seconds=2)

src/torchcodec/__init__.py

@@ -4,6 +4,9 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-from . import decoders, samplers  # noqa  # noqa
+# Note: usort wants to put Frame and FrameBatch after decoders and samplers,
+# but that results in circular import.
+from ._frame import Frame, FrameBatch  # usort:skip # noqa
+from . import decoders, samplers  # noqa
 
 __version__ = "0.0.4.dev"

src/torchcodec/_frame.py

@@ -0,0 +1,65 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+import dataclasses
+from dataclasses import dataclass
+from typing import Iterable, Iterator, Union
+
+from torch import Tensor
+
+
+def _frame_repr(self):
+    # Utility to replace Frame and FrameBatch __repr__ method. This prints the
+    # shape of the .data tensor rather than printing the (potentially very long)
+    # data tensor itself.
+    s = self.__class__.__name__ + ":\n"
+    spaces = "  "
+    for field in dataclasses.fields(self):
+        field_name = field.name
+        field_val = getattr(self, field_name)
+        if field_name == "data":
+            field_name = "data (shape)"
+            field_val = field_val.shape
+        s += f"{spaces}{field_name}: {field_val}\n"
+    return s
+
+
+@dataclass
+class Frame(Iterable):
+    """A single video frame with associated metadata."""
+
+    data: Tensor
+    """The frame data as (3-D ``torch.Tensor``)."""
+    pts_seconds: float
+    """The :term:`pts` of the frame, in seconds (float)."""
+    duration_seconds: float
+    """The duration of the frame, in seconds (float)."""
+
+    def __iter__(self) -> Iterator[Union[Tensor, float]]:
+        for field in dataclasses.fields(self):
+            yield getattr(self, field.name)
+
+    def __repr__(self):
+        return _frame_repr(self)
+
+
+@dataclass
+class FrameBatch(Iterable):
+    """Multiple video frames with associated metadata."""
+
+    data: Tensor
+    """The frames data as (4-D ``torch.Tensor``)."""
+    pts_seconds: Tensor
+    """The :term:`pts` of the frame, in seconds (1-D ``torch.Tensor`` of floats)."""
+    duration_seconds: Tensor
+    """The duration of the frame, in seconds (1-D ``torch.Tensor`` of floats)."""
+
+    def __iter__(self) -> Iterator[Union[Tensor, float]]:
+        for field in dataclasses.fields(self):
+            yield getattr(self, field.name)
+
+    def __repr__(self):
+        return _frame_repr(self)

src/torchcodec/decoders/__init__.py

@@ -5,6 +5,6 @@
 # LICENSE file in the root directory of this source tree.
 
 from ._core import VideoStreamMetadata
-from ._video_decoder import Frame, FrameBatch, VideoDecoder  # noqa
+from ._video_decoder import VideoDecoder  # noqa
 
 SimpleVideoDecoder = VideoDecoder

src/torchcodec/decoders/_video_decoder.py

@@ -4,71 +4,15 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-import dataclasses
 import numbers
-from dataclasses import dataclass
 from pathlib import Path
-from typing import Iterable, Iterator, Literal, Tuple, Union
+from typing import Literal, Tuple, Union
 
 from torch import Tensor
 
+from torchcodec import Frame, FrameBatch
 from torchcodec.decoders import _core as core
 
-
-def _frame_repr(self):
-    # Utility to replace Frame and FrameBatch __repr__ method. This prints the
-    # shape of the .data tensor rather than printing the (potentially very long)
-    # data tensor itself.
-    s = self.__class__.__name__ + ":\n"
-    spaces = "  "
-    for field in dataclasses.fields(self):
-        field_name = field.name
-        field_val = getattr(self, field_name)
-        if field_name == "data":
-            field_name = "data (shape)"
-            field_val = field_val.shape
-        s += f"{spaces}{field_name}: {field_val}\n"
-    return s
-
-
-@dataclass
-class Frame(Iterable):
-    """A single video frame with associated metadata."""
-
-    data: Tensor
-    """The frame data as (3-D ``torch.Tensor``)."""
-    pts_seconds: float
-    """The :term:`pts` of the frame, in seconds (float)."""
-    duration_seconds: float
-    """The duration of the frame, in seconds (float)."""
-
-    def __iter__(self) -> Iterator[Union[Tensor, float]]:
-        for field in dataclasses.fields(self):
-            yield getattr(self, field.name)
-
-    def __repr__(self):
-        return _frame_repr(self)
-
-
-@dataclass
-class FrameBatch(Iterable):
-    """Multiple video frames with associated metadata."""
-
-    data: Tensor
-    """The frames data as (4-D ``torch.Tensor``)."""
-    pts_seconds: Tensor
-    """The :term:`pts` of the frame, in seconds (1-D ``torch.Tensor`` of floats)."""
-    duration_seconds: Tensor
-    """The duration of the frame, in seconds (1-D ``torch.Tensor`` of floats)."""
-
-    def __iter__(self) -> Iterator[Union[Tensor, float]]:
-        for field in dataclasses.fields(self):
-            yield getattr(self, field.name)
-
-    def __repr__(self):
-        return _frame_repr(self)
-
-
 _ERROR_REPORTING_INSTRUCTIONS = """
 This should never happen. Please report an issue following the steps in
 https://github.com/pytorch/torchcodec/issues/new?assignees=&labels=&projects=&template=bug-report.yml.

src/torchcodec/samplers/_implem.py

@@ -2,7 +2,8 @@
 
 import torch
 
-from torchcodec.decoders import Frame, FrameBatch, VideoDecoder
+from torchcodec import Frame, FrameBatch
+from torchcodec.decoders import VideoDecoder
 
 
 def _validate_params(

test/samplers/test_samplers.py

@@ -5,7 +5,8 @@
 import pytest
 import torch
 
-from torchcodec.decoders import FrameBatch, VideoDecoder
+from torchcodec import FrameBatch
+from torchcodec.decoders import VideoDecoder
 from torchcodec.samplers import clips_at_random_indices, clips_at_regular_indices
 from torchcodec.samplers._implem import _build_all_clips_indices, _POLICY_FUNCTIONS