| /external/tensorflow/tensorflow/contrib/lite/kernels/ |
| softmax_test.cc | 81 const int input_size = 5; local
88 SoftmaxOpModel m(batch_size, input_size, beta);
90 m.SetInput(0, input_buffer, input_buffer + input_size * batch_size);
94 std::unique_ptr<float[]> output_buffer(new float[input_size * batch_size]);
95 static tflite::Dims<4> input_dims = {{input_size, 1, 1, batch_size},
96 {1, 0, 0, input_size}};
102 output_buffer.get() + input_size * batch_size);
109 const int input_size = 5; local
116 SoftmaxOpModel m(batch_size, input_size, beta);
118 m.SetInput(0, input_buffer, input_buffer + input_size * batch_size)
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/kernels/internal/ |
| kernel_utils.h | 34 int input_size, int num_units, int batch_size,
|
| kernel_utils.cc | 22 int input_size, int num_units, int batch_size,
30 input_weights_ptr, num_units, input_size, input_ptr_batch, batch_size,
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| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| rnn.mod.py | 19 input_size = 8 variable
23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
184 input_sequence_size = int(len(test_inputs) / input_size / batches)
189 input_begin = i * input_size
190 input_end = input_begin + input_size
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| svdf.mod.py | 21 input_size = 3 variable
26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size))
132 batch_start = i * input_size * batches
133 batch_end = batch_start + input_size * batches
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| svdf2.mod.py | 21 input_size = 3 variable
26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size))
147 batch_start = i * input_size * batches
148 batch_end = batch_start + input_size * batches
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| rnn_state.mod.py | 19 input_size = 8 variable
23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
|
| svdf_state.mod.py | 19 input_size = 3 variable
24 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| rnn_relaxed.mod.py | 19 input_size = 8 variable
23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
185 input_sequence_size = int(len(test_inputs) / input_size / batches)
190 input_begin = i * input_size
191 input_end = input_begin + input_size
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| svdf2_relaxed.mod.py | 21 input_size = 3 variable
26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size))
148 batch_start = i * input_size * batches
149 batch_end = batch_start + input_size * batches
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| svdf_relaxed.mod.py | 21 input_size = 3 variable
26 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size))
133 batch_start = i * input_size * batches
134 batch_end = batch_start + input_size * batches
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| rnn_state_relaxed.mod.py | 19 input_size = 8 variable
23 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
24 weights = Input("weights", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
|
| svdf_state_relaxed.mod.py | 19 input_size = 3 variable
24 input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (batches, input_size))
25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size))
|
| /external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
| graph_compute_order.py | 48 'NodeInfo', field_names=['order', 'node', 'input_size', 'output_size'])
96 input_size: Tensor spatial resolution at input of current node.
100 return (node_info[current].order, node_info[current].input_size,
107 input_size = None
109 node_info[current] = _node_info(order, node_def, input_size, output_size)
110 return (order, input_size, output_size)
112 input_size = None
131 input_size = parent_output_size
135 logging.vlog(3, 'input_size = %s', input_size)
[all...] |
| /external/brotli/c/enc/ |
| compress_fragment_two_pass.h | 31 REQUIRES: "input_size" is greater than zero, or "is_last" is 1.
32 REQUIRES: "input_size" is less or equal to maximal metablock size (1 << 24).
37 OUTPUT: maximal copy distance <= |input_size|
41 size_t input_size,
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| compress_fragment.h | 39 REQUIRES: "input_size" is greater than zero, or "is_last" is 1.
40 REQUIRES: "input_size" is less or equal to maximal metablock size (1 << 24).
43 OUTPUT: maximal copy distance <= |input_size|
47 size_t input_size,
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| /external/mesa3d/src/gallium/drivers/r600/ |
| evergreen_compute_internal.h | 42 unsigned input_size; member in struct:r600_pipe_compute
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| /external/tensorflow/tensorflow/core/kernels/ |
| fractional_max_pool_op.cc | 82 std::vector<int> input_size(tensor_in_and_out_dims);
85 input_size[i] = tensor_in.dim_size(i);
92 static_cast<int>(floor(input_size[i] / pooling_ratio_[i]));
101 height_cum_seq = GeneratePoolingSequence(input_size[1], output_size[1],
103 width_cum_seq = GeneratePoolingSequence(input_size[2], output_size[2],
125 ConstEigenMatrixMap in_mat(tensor_in.flat<T>().data(), input_size[3],
126 input_size[2] * input_size[1] * input_size[0]);
151 const int64 height_max = input_size[1] - 1
[all...] |
| sparse_slice_op.cc | 35 const Tensor& input_size = context->input(4); variable
53 OP_REQUIRES(context, TensorShapeUtils::IsVector(input_size.shape()),
56 input_size.shape().DebugString()));
64 OP_REQUIRES(context, input_dims == input_size.NumElements(),
67 " but got length ", input_size.NumElements()));
74 const gtl::ArraySlice<int64> size(input_size.flat<int64>().data(),
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| /external/libchrome/base/ |
| base64.cc | 29 size_t input_size = input.size(); local
30 size_t output_size = modp_b64_decode(&(temp[0]), input.data(), input_size);
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| index_ops_kernel_argmax_float_1d.cc | 32 int64 input_size = *static_cast<int64*>(data[1]); local
34 Eigen::DSizes<Eigen::DenseIndex, 1> in_eig_sizes(input_size);
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| /external/tensorflow/tensorflow/contrib/lite/toco/tensorflow_graph_matching/ |
| cluster.cc | 36 for (int i = 0; i < node.input_size(); i++) {
42 for (int i = 0; i < node.input_size(); i++) {
|
| /art/compiler/optimizing/ |
| nodes_shared.cc | 48 int input_size = DataType::Size(input_type); local
49 int min_size = std::min(result_size, input_size);
58 (input_type == DataType::Type::kUint8 && input_size < result_size)) {
61 (input_type == DataType::Type::kUint16 && input_size < result_size)) {
|
| /external/brotli/research/ |
| find_opt_references.cc | 43 void ReadInput(FILE* fin, input_type* storage, size_t input_size) {
51 assert(last_pos == input_size);
208 int input_size = ftell(fin); local
210 printf("The file size is %u bytes\n", input_size);
212 input_type* storage = new input_type[input_size];
214 ReadInput(fin, storage, input_size);
217 sarray_type* sarray = new sarray_type[input_size];
218 saisxx(storage, sarray, input_size);
222 uint32_t* pos = new uint32_t[input_size];
224 lcp_type* lcp = new lcp_type[input_size];
[all...] |
| /external/brotli/c/include/brotli/ |
| encode.h | 231 * Calculates the output size bound for the given @p input_size.
238 * @param input_size size of projected input
241 BROTLI_ENC_API size_t BrotliEncoderMaxCompressedSize(size_t input_size);
249 * @note If ::BrotliEncoderMaxCompressedSize(@p input_size) returns non-zero
255 * @param input_size size of @p input_buffer
256 * @param input_buffer input data buffer with at least @p input_size
267 int quality, int lgwin, BrotliEncoderMode mode, size_t input_size,
268 const uint8_t input_buffer[BROTLI_ARRAY_PARAM(input_size)],
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