| /external/mesa3d/prebuilt-intermediates/nir/ |
| D | nir_opcodes.c | 10 .input_sizes = {
24 .input_sizes = {
38 .input_sizes = {
52 .input_sizes = {
66 .input_sizes = {
80 .input_sizes = {
94 .input_sizes = {
108 .input_sizes = {
122 .input_sizes = {
136 .input_sizes = {
[all …]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | conv2d_test.py | 38 input_sizes=None, argument
56 total_size_1 = np.prod(input_sizes)
58 x1 = np.arange(1, total_size_1 + 1, dtype=np.float32).reshape(input_sizes)
66 t1 = array_ops.placeholder(dtypes.float32, shape=input_sizes)
85 input_sizes=[1, 2, 3, 3],
95 input_sizes=[1, 2, 3, 3],
104 input_sizes=[1, 4, 4, 1],
117 input_sizes=[1, 2, 3, 3],
126 input_sizes=[1, 2, 3, 3],
136 input_sizes=[1, 2, 3, 3],
[all …]
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| D | pooling_ops_3d_test.py | 46 def _VerifyValues(self, pool_func, input_sizes, window, strides, padding, argument
59 for s in input_sizes:
64 x = x.reshape(input_sizes)
81 input_sizes=[1, 3, 3, 3, 3],
91 input_sizes=[1, 2, 2, 4, 3],
101 input_sizes=[1, 5, 8, 1, 1],
111 input_sizes=[1, 3, 3, 3, 3],
121 input_sizes=[1, 2, 2, 3, 3],
131 input_sizes=[1, 5, 8, 1, 1],
151 input_sizes=[1, 5, 27, 27, 64],
[all …]
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| D | pooling_ops_test.py | 74 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding, argument
87 total_size = np.prod(input_sizes)
91 x = x.reshape(input_sizes)
110 def _VerifyValues(self, pool_func, input_sizes, ksize, strides, padding, argument
124 self._VerifyOneTest(pool_func, input_sizes, ksize, strides, padding,
130 input_sizes=[1, 3, 3, 3],
139 input_sizes=[1, 2, 3, 3],
156 input_sizes=[1, 2, 2, 1],
165 input_sizes=[1, 4, 4, 1],
172 input_sizes=[1, 4, 4, 1],
[all …]
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| D | depthwise_conv_op_test.py | 70 input_sizes = [[4, 5, 5, 48], [4, 8, 8, 84], [4, 17, 17, 48], [4, 9, 27, 8],
85 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
100 input_sizes = [[2, 5, 8, 1], [4, 5, 5, 1], [2, 4, 4, 2], [1, 15, 15, 2],
112 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
318 def _CompareBackpropInput(self, input_sizes, filter_sizes, output_sizes, argument
325 t0 = constant_op.constant(input_sizes, shape=[len(input_sizes)])
353 def _CompareBackpropFilter(self, input_sizes, filter_sizes, output_sizes, argument
355 x0 = np.random.rand(*input_sizes).astype(np.float32)
360 t0 = array_ops.placeholder(np.float32, shape=input_sizes)
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | pooling_ops_3d_test.py | 48 def _VerifyOneTest(self, pool_func, input_sizes, window, strides, padding, argument
63 for s in input_sizes:
69 t = constant_op.constant(x, shape=input_sizes)
89 def _VerifyValues(self, pool_func, input_sizes, window, strides, argument
92 self._VerifyOneTest(pool_func, input_sizes, window, strides, padding,
99 input_sizes=[1, 3, 3, 3, 3],
109 input_sizes=[1, 2, 2, 4, 3],
119 input_sizes=[1, 5, 8, 1, 1],
129 input_sizes=[1, 3, 3, 3, 3],
139 input_sizes=[1, 2, 2, 3, 3],
[all …]
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| D | pooling_ops_test.py | 76 input_sizes = [[32, 71, 71, 192], [32, 35, 35, 288], [32, 17, 17, 1248],
83 for i in input_sizes:
88 for n, i, f, o, s, p in zip(names, input_sizes, filter_sizes, output_sizes,
95 def _VerifyOneType(self, pool_func, input_sizes, ksize, strides, padding, argument
112 for s in input_sizes:
122 if input_sizes[-1] % 4 != 0:
123 tf_logging.info("Skipping test for depth %d", input_sizes[-1])
126 input_sizes, total_size, pool_func, ksize, strides)
131 t = constant_op.constant(x, shape=input_sizes, dtype=data_type)
171 def _VerifyOneTest(self, pool_func, input_sizes, ksize, strides, padding, argument
[all …]
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| D | conv_ops_test.py | 59 input_sizes = [[4, 5, 5, 1248], [4, 8, 8, 384], [4, 8, 8, 384],
122 for i in input_sizes:
140 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
520 def _RunAndVerifyBackpropInput(self, input_sizes, filter_sizes, output_sizes, argument
535 input_sizes = test_util.NHWCToNCHW(input_sizes)
536 t0 = constant_op.constant(input_sizes, shape=[len(input_sizes)])
554 def _CompareBackpropInput(self, input_sizes, filter_sizes, output_sizes, argument
562 new_input_sizes = test_util.NHWCToNCHW(input_sizes)
564 new_input_sizes = input_sizes
597 input_sizes=[1, 2, 3, 1],
[all …]
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| D | depthwise_conv_op_test.py | 40 input_sizes = [[4, 5, 5, 48], [4, 8, 8, 84], [4, 17, 17, 48], [4, 9, 27, 8],
55 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
70 input_sizes = [[2, 5, 8, 1], [4, 5, 5, 1], [2, 4, 4, 2], [1, 15, 15, 2],
82 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
454 def _CompareBackpropInputFloat(self, input_sizes, filter_sizes, output_sizes, argument
461 t0 = constant_op.constant(input_sizes, shape=[len(input_sizes)])
474 def _CompareBackpropInputDouble(self, input_sizes, filter_sizes, output_sizes, argument
481 t0 = constant_op.constant(input_sizes, shape=[len(input_sizes)])
505 def _CompareBackpropFilterFloat(self, input_sizes, filter_sizes, output_sizes, argument
507 x0 = np.random.rand(*input_sizes).astype(np.float32)
[all …]
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| D | neon_depthwise_conv_op_test.py | 38 input_sizes = [[4, 5, 5, 48], [4, 8, 8, 84], [4, 17, 17, 48], [4, 35, 35, 2],
50 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
65 input_sizes = [[2, 5, 8, 1], [4, 5, 5, 1], [2, 4, 4, 2], [1, 15, 15, 2],
77 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
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| /external/mesa3d/src/compiler/nir/ |
| D | nir_opcodes.py | 35 def __init__(self, name, output_size, output_type, input_sizes, argument
69 assert isinstance(input_sizes, list)
70 assert isinstance(input_sizes[0], int)
75 assert len(input_sizes) == len(input_types)
77 for size in input_sizes:
82 self.num_inputs = len(input_sizes)
85 self.input_sizes = input_sizes
107 def opcode(name, output_size, output_type, input_sizes, input_types, argument
110 opcodes[name] = Opcode(name, output_size, output_type, input_sizes,
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| D | nir_lower_alu_to_scalar.c | 46 unsigned num_components = nir_op_infos[instr->op].input_sizes[0]; in lower_reduction()
221 assert(nir_op_infos[instr->op].input_sizes[i] < 2); in lower_alu_instr_scalar()
222 unsigned src_chan = (nir_op_infos[instr->op].input_sizes[i] == 1 ? in lower_alu_instr_scalar()
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| D | nir_search.c | 114 if (nir_op_infos[instr->op].input_sizes[src] != 0) { in match_value()
115 num_components = nir_op_infos[instr->op].input_sizes[src]; in match_value()
468 if (nir_op_infos[alu->op].input_sizes[i] != 0) in construct_value()
469 num_components = nir_op_infos[alu->op].input_sizes[i]; in construct_value()
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| /external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
| D | graph_compute_order_test.py | 84 input_sizes = {}
92 input_sizes[node.name] = input_size
99 self.assertIn(k, input_sizes)
100 self.assertEqual(input_sizes[k], v)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | conv_grad_input_ops.cc | 221 const Tensor& input_sizes = context->input(0); in Compute() local
225 context, TensorShapeUtils::IsVector(input_sizes.shape()), in Compute()
228 input_sizes.dims())); in Compute()
231 input_sizes.vec<int32>(), &input_shape)); in Compute()
336 const Tensor& input_sizes = context->input(0); in Compute() local
340 context, TensorShapeUtils::IsVector(input_sizes.shape()), in Compute()
343 input_sizes.dims())); in Compute()
346 input_sizes.vec<int32>(), &input_shape)); in Compute()
654 const Tensor& input_sizes = context->input(0); in Compute() local
658 context, TensorShapeUtils::IsVector(input_sizes.shape()), in Compute()
[all …]
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| D | depthwise_conv_grad_op.cc | 554 const Tensor& input_sizes = context->input(0); in Compute() local
557 context, TensorShapeUtils::IsVector(input_sizes.shape()), in Compute()
560 input_sizes.dims())); in Compute()
562 const int32* in_sizes_data = input_sizes.template flat<int32>().data(); in Compute()
563 for (int i = 0; i < input_sizes.NumElements(); ++i) { in Compute()
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| /external/tensorflow/tensorflow/core/kernels/hexagon/ |
| D | hexagon_control_wrapper.cc | 99 std::vector<int> input_sizes; in Init() local
112 input_sizes.emplace_back(static_cast<int>(buf_size)); in Init()
129 input_sizes.size(), input_sizes.data(), output_sizes.size(), in Init()
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| D | soc_interface.h | 47 bool soc_interface_AllocateInOutNodeBuffers(int input_count, int* input_sizes,
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| /external/tensorflow/tensorflow/contrib/hvx/hexagon_controller/src_soc_interface/ |
| D | soc_interface.c | 92 bool soc_interface_AllocateInOutNodeBuffers(int input_count, int* input_sizes, in soc_interface_AllocateInOutNodeBuffers() argument
97 input_count, input_sizes, output_count, output_sizes); in soc_interface_AllocateInOutNodeBuffers()
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| /external/eigen/bench/tensors/ |
| D | tensor_benchmarks.h | 418 Eigen::array<TensorIndex, 2> input_sizes; in convolution() local
419 input_sizes[0] = m_; in convolution()
420 input_sizes[1] = n_; in convolution()
421 TensorMap<Tensor<T, 2>, Eigen::Aligned> A(a_, input_sizes); in convolution()
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| /external/tensorflow/tensorflow/contrib/hvx/hexagon_controller/src_soc_interface/include/ |
| D | soc_interface.h | 48 bool soc_interface_AllocateInOutNodeBuffers(int input_count, int* input_sizes,
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| /external/tensorflow/tensorflow/core/grappler/costs/ |
| D | utils_test.cc | 83 NodeDef* input_sizes = graph.add_node(); in TEST_F() local
87 input_sizes); in TEST_F()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_ops.py | 1251 input_sizes=output_shape_,
1387 input_sizes = [
1393 input_sizes=input_sizes,
1475 input_sizes=output_shape_,
2536 input_sizes=output_shape_,
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| /external/tensorflow/tensorflow/contrib/fused_conv/python/ops/ |
| D | fused_conv2d_bias_activation_op_test.py | 48 input_sizes = [[4, 5, 5, 1248], [4, 8, 8, 384], [4, 8, 8, 384], [
124 for i in input_sizes:
142 for i, f, o, s, p in zip(input_sizes, filter_sizes, out_sizes, strides,
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| /external/tensorflow/tensorflow/contrib/hvx/hexagon_controller/src_impl/ |
| D | hexagon_controller.c | 281 int* input_sizes, in hexagon_controller_AllocateMultipleNodeDataBuffers() argument
287 hexagon_controller_AllocateInputNodeDataBuffers(i, input_sizes[i]); in hexagon_controller_AllocateMultipleNodeDataBuffers()
|