Add rand_augment processing layer #20716
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #20716 +/- ##
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+ Coverage 81.83% 81.95% +0.11%
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Files 552 553 +1
Lines 51363 51437 +74
Branches 7944 7953 +9
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+ Hits 42034 42155 +121
+ Misses 7375 7346 -29
+ Partials 1954 1936 -18
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* Specify window_length dtype requirement in tf.keras.ops.istft in math.py (#20728) The `window_length` parameter in `tf.keras.ops.istft` requires `tf.int32` dtype, but this isn't documented. This can cause unexpected `ValueError` when using `tf.int64` and `tf.int16` Here is the Example case: ``` import tensorflow as tf input_dict = { 'stfts': tf.constant([[-0.87817144+1.14583987j, -0.32066484+0.25565411j]], dtype=tf.complex128), 'frame_length': tf.constant(256, dtype=tf.int16), 'frame_step': tf.constant(5120,dtype=tf.int64) } result = tf.signal.inverse_stft(**input_dict) print(result) ``` The code throws the following error: ``` ValueError: window_length: Tensor conversion requested dtype int32 for Tensor with dtype int64 ``` * Add rand_augment processing layer (#20716) * Add rand_augment init * Update rand_augment init * Add rand_augment * Add NotImplementedError * Add some test cases * Fix failed test case * Update rand_augment * Update rand_augment test * Fix random_rotation bug * Add build method to supress warning. * Add implementation for transform_bboxes * Fixing batch_dim_name attribute (#20674) * fixing wrong trainer assumption that batch dim is always the first one in the mesh * need functools partial * lint * fix test failure when distribution=None * lint2 * fix for test failure * added data sharding for 3D+ meshes * lint3 * added @Property for batch_dim_name + refactoring * fix typo * Add support for `dtype` / `DTypePolicy` to `JaxLayer` and `FlaxLayer`. (#20732) The `dtype` / `DTypePolicy` is applied to all float variables. * Allow dynamic shape in `STFTSpectrogram` layer. (#20736) by simply using `ops.shape(x)` instead of `x.shape`. * Remove duplicate export tests in `model_test`. (#20735) The same tests exist at: - https://github.com/keras-team/keras/blob/master/keras/src/export/saved_model_test.py#L66 - https://github.com/keras-team/keras/blob/master/keras/src/export/onnx_test.py#L62 The goal is to isolate the use of `onnxruntime` to a single file, `onnx_test.py`. * Add OpenVINO into README.md (#20739) * Add OpenVINO into README.md Signed-off-by: Kazantsev, Roman <[email protected]> * Update README.md --------- Signed-off-by: Kazantsev, Roman <[email protected]> * Multiple Example Title has removed in metrics.MeanIoU method (#20738) Multiple Example Title has removed in metrics.MeanIoU method --------- Signed-off-by: Kazantsev, Roman <[email protected]> Co-authored-by: LakshmiKalaKadali <[email protected]> Co-authored-by: Ugeun Park <[email protected]> Co-authored-by: Martin Görner <[email protected]> Co-authored-by: hertschuh <[email protected]> Co-authored-by: Roman Kazantsev <[email protected]> Co-authored-by: LavanyaKV1234 <[email protected]>
divyashreepathihalli
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Jan 9, 2025
* Specify window_length dtype requirement in tf.keras.ops.istft in math.py (#20728) The `window_length` parameter in `tf.keras.ops.istft` requires `tf.int32` dtype, but this isn't documented. This can cause unexpected `ValueError` when using `tf.int64` and `tf.int16` Here is the Example case: ``` import tensorflow as tf input_dict = { 'stfts': tf.constant([[-0.87817144+1.14583987j, -0.32066484+0.25565411j]], dtype=tf.complex128), 'frame_length': tf.constant(256, dtype=tf.int16), 'frame_step': tf.constant(5120,dtype=tf.int64) } result = tf.signal.inverse_stft(**input_dict) print(result) ``` The code throws the following error: ``` ValueError: window_length: Tensor conversion requested dtype int32 for Tensor with dtype int64 ``` * Add rand_augment processing layer (#20716) * Add rand_augment init * Update rand_augment init * Add rand_augment * Add NotImplementedError * Add some test cases * Fix failed test case * Update rand_augment * Update rand_augment test * Fix random_rotation bug * Add build method to supress warning. * Add implementation for transform_bboxes * Fixing batch_dim_name attribute (#20674) * fixing wrong trainer assumption that batch dim is always the first one in the mesh * need functools partial * lint * fix test failure when distribution=None * lint2 * fix for test failure * added data sharding for 3D+ meshes * lint3 * added @Property for batch_dim_name + refactoring * fix typo * Add support for `dtype` / `DTypePolicy` to `JaxLayer` and `FlaxLayer`. (#20732) The `dtype` / `DTypePolicy` is applied to all float variables. * Allow dynamic shape in `STFTSpectrogram` layer. (#20736) by simply using `ops.shape(x)` instead of `x.shape`. * Remove duplicate export tests in `model_test`. (#20735) The same tests exist at: - https://github.com/keras-team/keras/blob/master/keras/src/export/saved_model_test.py#L66 - https://github.com/keras-team/keras/blob/master/keras/src/export/onnx_test.py#L62 The goal is to isolate the use of `onnxruntime` to a single file, `onnx_test.py`. * Add OpenVINO into README.md (#20739) * Add OpenVINO into README.md Signed-off-by: Kazantsev, Roman <[email protected]> * Update README.md --------- Signed-off-by: Kazantsev, Roman <[email protected]> * Multiple Example Title has removed in metrics.MeanIoU method (#20738) Multiple Example Title has removed in metrics.MeanIoU method --------- Signed-off-by: Kazantsev, Roman <[email protected]> Co-authored-by: LakshmiKalaKadali <[email protected]> Co-authored-by: Ugeun Park <[email protected]> Co-authored-by: Martin Görner <[email protected]> Co-authored-by: hertschuh <[email protected]> Co-authored-by: Roman Kazantsev <[email protected]> Co-authored-by: LavanyaKV1234 <[email protected]>
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I have implemented the transform_images method in the RandAugment image processing layer. If this pull request is accepted, I can proceed with implementing the transform_bounding_boxes method as well.
here is my gist