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Searched refs:kernel_shape (Results 1 – 18 of 18) sorted by relevance

/external/tensorflow/tensorflow/python/keras/utils/
Dconv_utils_test.py168 kernel_shape = input_shape
177 kernel_shape,
185 kernel_shape = (1,) * ndims
195 kernel_shape,
204 kernel_shape = (1,) * ndims
216 kernel_shape,
225 kernel_shape = (1,) * ndims
239 kernel_shape,
251 kernel_shape = [1] * ndims
252 kernel_shape[d] = input_shape[d]
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Dconv_utils.py214 def conv_kernel_mask(input_shape, kernel_shape, strides, padding): argument
266 if isinstance(kernel_shape, int):
267 kernel_shape = (kernel_shape,) * in_dims
271 kernel_dims = len(kernel_shape)
278 output_shape = conv_output_shape(input_shape, kernel_shape, strides, padding)
285 input_axes_ticks = conv_connected_inputs(input_shape, kernel_shape,
293 def conv_kernel_idxs(input_shape, kernel_shape, strides, padding, filters_in, argument
348 if isinstance(kernel_shape, int):
349 kernel_shape = (kernel_shape,) * in_dims
353 kernel_dims = len(kernel_shape)
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/external/tensorflow/tensorflow/python/kernel_tests/
Dmorphological_ops_test.py185 def _ConstructAndTestGradient(self, image_shape, kernel_shape, strides, rates, argument
197 assert image_shape[3] == kernel_shape[2]
201 kernel = np.random.random_sample(kernel_shape).astype(np.float32)
208 kernel, shape=kernel_shape, name="filter")
236 kernel_shape=[1, 1, 1],
245 kernel_shape=[1, 1, 1],
254 kernel_shape=[1, 1, 2],
263 kernel_shape=[2, 2, 1],
272 kernel_shape=[2, 2, 1],
281 kernel_shape=[2, 2, 1],
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/external/tensorflow/tensorflow/compiler/xla/service/cpu/
Dir_emission_utils.cc54 const Shape& kernel_shape = convolution.operand(1)->shape(); in PotentiallyImplementedAsEigenConvolution() local
62 if (!is_aligned(input_shape) || !is_aligned(kernel_shape) || in PotentiallyImplementedAsEigenConvolution()
68 ShapeUtil::IsZeroElementArray(kernel_shape)) { in PotentiallyImplementedAsEigenConvolution()
73 ShapeUtil::SameElementTypeIgnoringFpPrecision(input_shape, kernel_shape)); in PotentiallyImplementedAsEigenConvolution()
110 kernel_shape.dimensions_size() - 2 && in PotentiallyImplementedAsEigenConvolution()
112 kernel_shape.dimensions_size() - 1; in PotentiallyImplementedAsEigenConvolution()
Dir_emitter.cc913 const Shape& kernel_shape = convolution->operand(1)->shape(); in HandleConvolution() local
915 kernel_shape.dimensions(dnums.kernel_spatial_dimensions(0)); in HandleConvolution()
919 : kernel_shape.dimensions(dnums.kernel_spatial_dimensions(1)); in HandleConvolution()
921 kernel_shape.dimensions(dnums.kernel_input_feature_dimension()); in HandleConvolution()
923 kernel_shape.dimensions(dnums.kernel_output_feature_dimension()); in HandleConvolution()
/external/tensorflow/tensorflow/python/keras/layers/
Dlocal.py175 self.kernel_shape = (self.output_length, self.kernel_size[0] * input_dim,
179 shape=self.kernel_shape,
187 self.kernel_shape = (input_dim, input_length, self.filters,
190 self.kernel_shape = (input_length, input_dim, self.output_length,
194 shape=self.kernel_shape,
202 kernel_shape=self.kernel_size,
209 self.kernel_shape = (self.output_length * self.filters,
215 kernel_shape=self.kernel_size,
275 self.kernel_shape,
481 self.kernel_shape = (output_row * output_col, self.kernel_size[0] *
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Dconvolutional_recurrent.py282 shape = list(self.cell.kernel_shape)
553 kernel_shape = self.kernel_size + (input_dim, self.filters * 4)
554 self.kernel_shape = kernel_shape
557 self.kernel = self.add_weight(shape=kernel_shape,
Deinsum_dense.py146 kernel_shape, bias_shape, self.full_output_shape = shape_data
149 shape=kernel_shape,
Dconvolutional.py196 kernel_shape = self.kernel_size + (input_channel // self.groups,
201 shape=kernel_shape,
975 kernel_shape = self.kernel_size + (self.filters, input_dim)
979 shape=kernel_shape,
1246 kernel_shape = self.kernel_size + (self.filters, input_dim)
1250 shape=kernel_shape,
1555 kernel_shape = self.kernel_size + (self.filters, input_dim)
1560 shape=kernel_shape,
/external/tensorflow/tensorflow/python/profiler/internal/
Dflops_registry.py319 kernel_shape = list(node.attr["ksize"].list.i)
320 kernel_area = _list_product(kernel_shape)
344 kernel_shape = list(node.attr["ksize"].list.i)
345 kernel_area = _list_product(kernel_shape)
372 kernel_shape = list(node.attr["ksize"].list.i)
373 kernel_area = _list_product(kernel_shape)
401 kernel_shape = graph_util.tensor_shape_from_node_def_name(graph,
403 kernel_shape.assert_is_fully_defined()
409 * kernel_shape.num_elements()
425 kernel_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dextract_image_patches_op.cc109 std::vector<int64> kernel_shape(num_dims, 1); in Compile() local
112 kernel_shape[i] = ksizes_[input_dim]; in Compile()
115 kernel_shape[num_spatial_dims] = 1; in Compile()
116 kernel_shape[num_spatial_dims + 1] = kernel_size * depth; in Compile()
124 kernel_shape); in Compile()
/external/tensorflow/tensorflow/python/keras/
Dconstraints.py242 kernel_shape = K.shape(kernel)[0]
243 start = K.cast(kernel_shape / 2, 'int32')
246 K.cast(math_ops.floormod(kernel_shape, 2), 'bool'),
251 K.cast(math_ops.floormod(kernel_shape, 2), 'bool'),
Dbackend.py5355 kernel_shape = kernel.shape.as_list()
5358 left_pad = dilation_rate * (kernel_shape[0] - 1)
5935 kernel_shape = int_shape(kernel)
5936 feature_dim = kernel_shape[1]
5937 channels_out = kernel_shape[-1]
Dbackend_test.py942 kernel_shape = (np.prod(output_shape),
949 kernel_cf = np.reshape(kernel, kernel_shape)
962 kernel_shape)
/external/XNNPACK/bench/
Dconvolution.cc875 arm_compute::TensorShape kernel_shape( in armcl_convolution_f32() local
881 kernel_shape, in armcl_convolution_f32()
924 reinterpret_cast<float*>(kernelTensor.buffer()) + kernel_shape.total_size(), in armcl_convolution_f32()
1023 kernel_shape.total_size(), in armcl_convolution_f32()
/external/tensorflow/tensorflow/compiler/tests/
Drandomized_tests.cc1632 Tensor kernel_shape = test::AsTensor<int32>(AsInt32s( in TEST_F() local
1638 .Input(kernel_shape) in TEST_F()
1706 Tensor kernel_shape = test::AsTensor<int32>( in TEST_F() local
1713 .Input(kernel_shape) in TEST_F()
1811 Tensor kernel_shape = test::AsTensor<int32>(AsInt32s( in TEST_F() local
1818 .Input(kernel_shape) in TEST_F()
/external/tensorflow/tensorflow/compiler/xrt/tests/
Draw_api_test.cc1504 auto kernel_shape = xla::ShapeUtil::MakeShape(xla::BF16, {3, 3, 5, 5}); in TEST() local
1508 xla::LayoutUtil::ClearLayout(&kernel_shape); in TEST()
1510 xla::ShapeUtil::MakeTupleShape({input_shape, kernel_shape}); in TEST()
/external/tensorflow/tensorflow/compiler/xla/service/
Dspace_to_batch_converter.cc2596 const auto& kernel_shape = kernel->shape(); in GetConvolutionDetails() local
2598 kernel_shape.dimensions(dim_numbers.kernel_spatial_dimensions( in GetConvolutionDetails()