From 7b357dd06b653b2b9b6ce88036e9a90cc77ca903 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Mon, 27 Apr 2020 21:23:58 -0700
Subject: [PATCH] Internal change
PiperOrigin-RevId: 308757298
Change-Id: I9ec9dfdd236a1ed796f82fd77e0afee777ca626d
---
.../python/keras/layers/convolutional.py | 15 ++++++-------
.../python/keras/layers/convolutional_test.py | 22 +++++++++++++++++++
2 files changed, 29 insertions(+), 8 deletions(-)
diff --git a/tensorflow/python/keras/layers/convolutional.py b/tensorflow/python/keras/layers/convolutional.py
index 476aaba6bb5..83bfb47c5b1 100644
--- a/tensorflow/python/keras/layers/convolutional.py
+++ b/tensorflow/python/keras/layers/convolutional.py
@@ -305,8 +305,9 @@ class Conv(Layer):
"""Recreate conv_op if necessary.
Check if the input_shape in call() is different from that in build().
- For the values that are not None, if they are different, recreate
- the _convolution_op to avoid the stateful behavior.
+ If the most-specific input shape describing the build and call shapes is not
+ equal to the shape we currently built with, then we need to rebuild the
+ _convolution_op to avoid incorrect behavior.
Args:
inputs: The input data to call() method.
@@ -315,12 +316,10 @@ class Conv(Layer):
`True` or `False` to indicate whether to recreate the conv_op.
"""
call_input_shape = inputs.get_shape()
- for axis in range(1, len(call_input_shape)):
- if (call_input_shape[axis] is not None
- and self._build_conv_op_input_shape[axis] is not None
- and call_input_shape[axis] != self._build_conv_op_input_shape[axis]):
- return True
- return False
+ # If the most specific compatible shape between _build_input_shape and
+ # call_input_shape is not _build_input_shape then we must re-build.
+ return self._build_conv_op_input_shape.most_specific_compatible_shape(
+ call_input_shape) != self._build_conv_op_input_shape
@keras_export('keras.layers.Conv1D', 'keras.layers.Convolution1D')
diff --git a/tensorflow/python/keras/layers/convolutional_test.py b/tensorflow/python/keras/layers/convolutional_test.py
index a36efd9da26..528bc14adf4 100644
--- a/tensorflow/python/keras/layers/convolutional_test.py
+++ b/tensorflow/python/keras/layers/convolutional_test.py
@@ -23,6 +23,8 @@ import numpy as np
from tensorflow.python import keras
from tensorflow.python.eager import context
+from tensorflow.python.eager import def_function
+from tensorflow.python.framework import tensor_spec
from tensorflow.python.framework import test_util
from tensorflow.python.keras import keras_parameterized
from tensorflow.python.keras import testing_utils
@@ -108,6 +110,26 @@ class Conv1DTest(keras_parameterized.TestCase):
_ = layer(inpt2).shape
self.assertEqual(outp1_shape, layer(inpt1).shape)
+ def test_conv1d_recreate_conv_unknown_dims(self):
+ with self.cached_session(use_gpu=True):
+ layer = keras.layers.Conv1D(filters=1,
+ kernel_size=3,
+ strides=1,
+ dilation_rate=2,
+ padding='causal')
+
+ inpt1 = np.random.normal(size=[1, 9, 1]).astype(np.float32)
+ inpt2 = np.random.normal(size=[1, 2, 1]).astype(np.float32)
+ outp1_shape = layer(inpt1).shape
+
+ @def_function.function(input_signature=[
+ tensor_spec.TensorSpec([1, None, 1])])
+ def fn(inpt):
+ return layer(inpt)
+
+ fn(inpt2)
+ self.assertEqual(outp1_shape, layer(inpt1).shape)
+
@keras_parameterized.run_all_keras_modes
class Conv2DTest(keras_parameterized.TestCase):