| /external/tensorflow/tensorflow/compiler/xla/ |
| D | window_util.cc | 51 /* static */ string ToString(const WindowDimension& dim) { in ToString() argument
54 string str = StrCat("(size=", dim.size()); in ToString()
55 if (dim.stride() != 1) { in ToString()
56 StrAppend(&str, ",stride=", dim.stride()); in ToString()
58 if (dim.padding_low() != 0) { in ToString()
59 StrAppend(&str, ",padding_low=", dim.padding_low()); in ToString()
61 if (dim.padding_high() != 0) { in ToString()
62 StrAppend(&str, ",padding_high=", dim.padding_high()); in ToString()
64 if (dim.base_dilation() != 1) { in ToString()
65 StrAppend(&str, ",base_dilation=", dim.base_dilation()); in ToString()
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| D | array_test.cc | 28 EXPECT_EQ(uninit.dim(0), 2); in TEST()
29 EXPECT_EQ(uninit.dim(1), 3); in TEST()
36 EXPECT_EQ(fullof7.dim(0), 1); in TEST()
37 EXPECT_EQ(fullof7.dim(1), 2); in TEST()
38 EXPECT_EQ(fullof7.dim(2), 3); in TEST()
40 for (int64 n0 = 0; n0 < fullof7.dim(0); ++n0) { in TEST()
41 for (int64 n1 = 0; n1 < fullof7.dim(1); ++n1) { in TEST()
42 for (int64 n2 = 0; n2 < fullof7.dim(2); ++n2) { in TEST()
52 EXPECT_EQ(arr.dim(0), 2); in TEST()
53 EXPECT_EQ(arr.dim(1), 3); in TEST()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | conv_grad_ops.cc | 46 int dim) const { in SpatialPadding()
50 0, static_cast<int>((output_size(dim) - 1) * stride(dim) + in SpatialPadding()
51 (filter_size(dim) - 1) * dilation(dim) + in SpatialPadding()
52 1 - input_size(dim))); in SpatialPadding()
62 int filter_spatial_dim, ConvBackpropSpatialDimension* dim) { in ConvBackpropExtractAndVerifyDimension() argument
63 dim->input_size = input_shape.dim_size(spatial_dim); in ConvBackpropExtractAndVerifyDimension()
64 dim->filter_size = filter_shape.dim_size(filter_spatial_dim); in ConvBackpropExtractAndVerifyDimension()
65 dim->output_size = output_shape.dim_size(spatial_dim); in ConvBackpropExtractAndVerifyDimension()
66 dim->stride = strides[spatial_dim]; in ConvBackpropExtractAndVerifyDimension()
67 dim->dilation = dilations[spatial_dim]; in ConvBackpropExtractAndVerifyDimension()
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| D | ragged_tensor_to_sparse_kernel.cc | 84 for (int dim = rt_nested_splits_len - 2; dim >= 0; --dim) { in Compute() local
85 while (IsCompleted(pos, dim, rt_nested_splits)) { in Compute()
86 pos[dim] += 1; in Compute()
91 for (int dim = 0; dim < index_prefix.size(); ++dim) { in Compute() local
92 int start = dim > 0 ? rt_nested_splits[dim - 1](pos[dim - 1]) : 0; in Compute()
93 index_prefix[dim] = pos[dim] - start; in Compute()
103 int dim = 0; in Compute() local
105 sparse_indices(next_index, dim++) = index; in Compute()
107 sparse_indices(next_index, dim++) = i; // index_middle in Compute()
109 sparse_indices(next_index, dim++) = index; in Compute()
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| D | mirror_pad_op.h | 126 for (int dim = 0; dim < Dims; ++dim) {
127 eigen_assert(padding_[dim].first + op.offset() <= dimensions_[dim]);
128 eigen_assert(padding_[dim].second + op.offset() <= dimensions_[dim]);
129 dimensions_[dim] += padding_[dim].first + padding_[dim].second;
170 for (int dim = 0; dim < Dims; ++dim) {
171 coords[dim] = ToInputCoord(coords[dim], dim);
190 int dim = -1;
194 dim = k;
201 dim = k;
210 if (dim < 0) {
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| D | unique_op_test.cc | 38 TensorProto GetRandomInt32TensorProto(int dim, int max_int) { in GetRandomInt32TensorProto() argument
41 tensor_proto.mutable_tensor_shape()->add_dim()->set_size(dim); in GetRandomInt32TensorProto()
43 for (int i = 0; i < dim; ++i) { in GetRandomInt32TensorProto()
50 TensorProto GetRandomInt32TensorProtoWithRepeat(int dim, int repeat, in GetRandomInt32TensorProtoWithRepeat() argument
54 tensor_proto.mutable_tensor_shape()->add_dim()->set_size(dim); in GetRandomInt32TensorProtoWithRepeat()
56 for (int i = 0; i < dim; ++i) { in GetRandomInt32TensorProtoWithRepeat()
65 static void BM_Unique_INT32(int iters, int dim, int max_int) { in BM_Unique_INT32() argument
69 Tensor input(DT_INT32, TensorShape({dim})); in BM_Unique_INT32()
70 CHECK(input.FromProto(GetRandomInt32TensorProto(dim, max_int))); in BM_Unique_INT32()
78 testing::BytesProcessed(static_cast<int64>(iters) * dim * sizeof(int32)); in BM_Unique_INT32()
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| D | scatter_nd_op_cpu_impl.h | 106 for (int dim = IXDIM - 1; dim >= 0; --dim) {
107 if (dim == IXDIM - 1) {
108 batch_strides[dim] = 1;
110 batch_strides[dim] =
111 batch_strides[dim + 1] * output_shape_prefix[dim + 1];
118 for (int dim = 0; dim < IXDIM; ++dim) {
119 const Index ix_d = internal::SubtleMustCopy(Tindices(loc, dim));
120 out_of_bounds |= !FastBoundsCheck(ix_d, output_shape_prefix[dim]);
121 i += ix_d * batch_strides[dim];
190 for (int dim = IXDIM - 1; dim >= 0; --dim) {
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| /external/tensorflow/tensorflow/compiler/tf2tensorrt/plugin/ |
| D | trt_plugin.cc | 39 nvinfer1::Dims dim; in PluginTensorRT() local
40 std::memcpy(&(dim.nbDims), buffer, sizeof(dim.nbDims)); in PluginTensorRT()
41 buffer += sizeof(dim.nbDims); in PluginTensorRT()
42 std::memcpy(dim.d, buffer, sizeof(dim.d)); in PluginTensorRT()
43 buffer += sizeof(dim.d); in PluginTensorRT()
44 std::memcpy(dim.type, buffer, sizeof(dim.type)); in PluginTensorRT()
45 buffer += sizeof(dim.type); in PluginTensorRT()
46 input_dim_list_.emplace_back(dim); in PluginTensorRT()
54 nvinfer1::Dims dim; in configure() local
55 dim.nbDims = inputs[index].nbDims; in configure()
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | lstm_layer_inference.config.pbtxt | 2 feed{ id{node_name:"inputs/x_seq_0/read"} shape{dim{size:128}dim{size:1024}} }
3 feed{ id{node_name:"inputs/x_seq_1/read"} shape{dim{size:128}dim{size:1024}} }
4 feed{ id{node_name:"inputs/x_seq_2/read"} shape{dim{size:128}dim{size:1024}} }
5 feed{ id{node_name:"inputs/x_seq_3/read"} shape{dim{size:128}dim{size:1024}} }
6 feed{ id{node_name:"inputs/x_seq_4/read"} shape{dim{size:128}dim{size:1024}} }
7 feed{ id{node_name:"inputs/pad_seq_0/read"} shape{dim{size:128}dim{size:1}} }
8 feed{ id{node_name:"inputs/pad_seq_1/read"} shape{dim{size:128}dim{size:1}} }
9 feed{ id{node_name:"inputs/pad_seq_2/read"} shape{dim{size:128}dim{size:1}} }
10 feed{ id{node_name:"inputs/pad_seq_3/read"} shape{dim{size:128}dim{size:1}} }
11 feed{ id{node_name:"inputs/pad_seq_4/read"} shape{dim{size:128}dim{size:1}} }
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| /external/tensorflow/tensorflow/core/grappler/utils/ |
| D | symbolic_shapes.cc | 27 dims.push_back(shape.dim(i).size()); in ShapeDims()
33 bool IsKnown(const TensorShapeProto::Dim& dim) { return dim.size() >= 0; } in IsKnown() argument
35 bool IsKnownSymbolically(const TensorShapeProto::Dim& dim) { in IsKnownSymbolically() argument
36 return dim.size() <= -2; in IsKnownSymbolically()
39 bool IsUnknown(const TensorShapeProto::Dim& dim) { return dim.size() == -1; } in IsUnknown() argument
44 shape.dim().begin(), shape.dim().end(), in ShapeIsSymbolicallyDefined()
45 [](const TensorShapeProto::Dim& dim) { return !IsUnknown(dim); }); in ShapeIsSymbolicallyDefined() argument
64 for (const auto& dim : shape.dim()) { in NumCoefficients() local
65 if (dim.size() < 0) { in NumCoefficients()
68 num_coefficients *= dim.size(); in NumCoefficients()
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| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| D | conv_grad_size_util.cc | 37 SpatialDimensionOutputSizeAndPadding dim; in GetWindowedOutputSize() local
40 dim.output_size = (input_size - effective_filter_size + stride) / stride; in GetWindowedOutputSize()
41 dim.pad_before = dim.pad_after = 0; in GetWindowedOutputSize()
44 dim.output_size = (input_size + stride - 1) / stride; in GetWindowedOutputSize()
46 std::max(int64{0}, (dim.output_size - 1) * stride + in GetWindowedOutputSize()
50 dim.pad_before = padding_needed / 2; in GetWindowedOutputSize()
51 dim.pad_after = padding_needed - dim.pad_before; in GetWindowedOutputSize()
54 if (dim.output_size < 0) { in GetWindowedOutputSize()
56 "Computed output size would be negative: ", dim.output_size, in GetWindowedOutputSize()
61 return dim; in GetWindowedOutputSize()
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| /external/tensorflow/tensorflow/core/profiler/internal/testdata/ |
| D | graph.pbtxt | 9 dim {
12 dim {
15 dim {
18 dim {
37 dim {
40 dim {
43 dim {
46 dim {
71 dim {
89 dim {
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| /external/tensorflow/tensorflow/core/profiler/internal/ |
| D | tfprof_tensor.h | 55 bool AddValue(const T& value, TFProfTensorProto* dim) { in AddValue() argument
61 dim->add_value_double(double_val); in AddValue()
63 "%.2f ", dim->value_double(dim->value_double_size() - 1)); in AddValue()
67 dim->add_value_int64(int64_val); in AddValue()
70 static_cast<int64>(dim->value_int64(dim->value_int64_size() - 1))); in AddValue()
72 dim->add_value_str(sstream.str()); in AddValue()
75 dim->value_str(dim->value_str_size() - 1) + "' "); in AddValue()
86 TFProfTensorProto* dim) { in BuildOutput() argument
96 dim->add_value_double(double_val); in BuildOutput()
98 "%.2f ", dim->value_double(dim->value_double_size() - 1)); in BuildOutput()
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| /external/eigen/test/ |
| D | umeyama.cpp | 91 void run_test(int dim, int num_elements) in run_test() argument
102 MatrixX R = randMatrixSpecialUnitary<Scalar>(dim); in run_test()
103 VectorX t = Scalar(50)*VectorX::Random(dim,1); in run_test()
105 MatrixX cR_t = MatrixX::Identity(dim+1,dim+1); in run_test()
106 cR_t.block(0,0,dim,dim) = c*R; in run_test()
107 cR_t.block(0,dim,dim,1) = t; in run_test()
109 MatrixX src = MatrixX::Random(dim+1, num_elements); in run_test()
110 src.row(dim) = Matrix<Scalar, 1, Dynamic>::Constant(num_elements, Scalar(1)); in run_test()
114 MatrixX cR_t_umeyama = umeyama(src.block(0,0,dim,num_elements), dst.block(0,0,dim,num_elements)); in run_test()
129 const int dim = Dimension; in run_fixed_size_test() local
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| D | geo_alignedbox.cpp | 32 const Index dim = _box.dim(); in alignedbox() local
34 VectorType p0 = VectorType::Random(dim); in alignedbox()
35 VectorType p1 = VectorType::Random(dim); in alignedbox()
37 p1 = VectorType::Random(dim); } in alignedbox()
40 BoxType b0(dim); in alignedbox()
41 BoxType b1(VectorType::Random(dim),VectorType::Random(dim)); in alignedbox()
60 BoxType box1(VectorType::Random(dim)); in alignedbox()
61 box1.extend(VectorType::Random(dim)); in alignedbox()
62 BoxType box2(VectorType::Random(dim)); in alignedbox()
63 box2.extend(VectorType::Random(dim)); in alignedbox()
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| /external/swiftshader/third_party/llvm-7.0/llvm/test/Transforms/LoopVectorize/X86/ |
| D | register-assumption.ll | 8 br label %loop_exit.dim.11.critedge
10 loop_exit.dim.11.critedge: ; preds = %loop_body.dim.0
14 br label %loop_header.dim.017.preheader
16 loop_header.dim.017.preheader: ; preds = %loop_exit.dim.016, %loop_exit.dim.11.c…
17 br label %loop_body.dim.018
19 loop_body.dim.018: ; preds = %loop_body.dim.018, %loop_header.dim.01…
20 …%invar_address.dim.019.0135 = phi i64 [ 0, %loop_header.dim.017.preheader ], [ %0, %loop_body.dim.…
24 %0 = add nuw nsw i64 %invar_address.dim.019.0135, 1
26 br i1 %1, label %loop_header.dim.017.preheader, label %loop_body.dim.018
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| /external/llvm/test/Transforms/LoopVectorize/X86/ |
| D | register-assumption.ll | 8 br label %loop_exit.dim.11.critedge
10 loop_exit.dim.11.critedge: ; preds = %loop_body.dim.0
14 br label %loop_header.dim.017.preheader
16 loop_header.dim.017.preheader: ; preds = %loop_exit.dim.016, %loop_exit.dim.11.c…
17 br label %loop_body.dim.018
19 loop_body.dim.018: ; preds = %loop_body.dim.018, %loop_header.dim.01…
20 …%invar_address.dim.019.0135 = phi i64 [ 0, %loop_header.dim.017.preheader ], [ %0, %loop_body.dim.…
24 %0 = add nuw nsw i64 %invar_address.dim.019.0135, 1
26 br i1 %1, label %loop_header.dim.017.preheader, label %loop_body.dim.018
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| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| D | cudnn_conv_rewriter.cc | 164 WindowDimension* dim = backward_conv_window.add_dimensions(); in MatchBackwardFilter() local
168 dim->set_size(filter_size); in MatchBackwardFilter()
170 dim->set_stride(conv->window().dimensions(i).window_dilation()); in MatchBackwardFilter()
173 dim->set_padding_low(conv->window().dimensions(i).padding_low()); in MatchBackwardFilter()
174 dim->set_base_dilation(1); in MatchBackwardFilter()
175 dim->set_window_dilation(1); in MatchBackwardFilter()
190 int64 padded_input_size = filter_size + (output_size - 1) * dim->stride(); in MatchBackwardFilter()
192 padded_input_size - input_size - dim->padding_low(); in MatchBackwardFilter()
193 int64 max_padding_high = min_padding_high + dim->stride() - 1; in MatchBackwardFilter()
194 CHECK_GE(dim->padding_low(), 0); in MatchBackwardFilter()
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| D | cudnn_conv_runner.cc | 159 for (const WindowDimension& dim : window.dimensions()) { in RunCudnnConvImpl() local
160 CHECK_EQ(dims_reversed, dim.window_reversal()); in RunCudnnConvImpl()
161 CHECK_EQ(dim.padding_low(), dim.padding_high()); in RunCudnnConvImpl()
162 CHECK_EQ(dim.base_dilation(), 1) in RunCudnnConvImpl()
165 CHECK_EQ(dim.window_dilation(), 1) in RunCudnnConvImpl()
186 for (int dim = 0; dim < num_dimensions; ++dim) { in RunCudnnConvImpl() local
189 static_cast<DimIndex>(effective_num_dimensions - dim - 1), in RunCudnnConvImpl()
190 input_shape.dimensions(dnums.input_spatial_dimensions(dim))); in RunCudnnConvImpl()
199 for (int dim = 0; dim < num_dimensions; ++dim) { in RunCudnnConvImpl() local
201 static_cast<DimIndex>(effective_num_dimensions - dim - 1), in RunCudnnConvImpl()
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| /external/eigen/unsupported/test/ |
| D | cxx11_tensor_argmax.cpp | 166 for (int dim = 0; dim < 4; ++dim) { in test_argmax_dim() local
177 if (ix[dim] != 0) continue; in test_argmax_dim()
185 tensor_argmax = tensor.argmax(dim); in test_argmax_dim()
188 ptrdiff_t(2*3*5*7 / tensor.dimension(dim))); in test_argmax_dim()
199 if (ix[dim] != tensor.dimension(dim) - 1) continue; in test_argmax_dim()
207 tensor_argmax = tensor.argmax(dim); in test_argmax_dim()
210 ptrdiff_t(2*3*5*7 / tensor.dimension(dim))); in test_argmax_dim()
213 VERIFY_IS_EQUAL(tensor_argmax.data()[n], tensor.dimension(dim) - 1); in test_argmax_dim()
224 for (int dim = 0; dim < 4; ++dim) { in test_argmin_dim() local
235 if (ix[dim] != 0) continue; in test_argmin_dim()
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| /external/tensorflow/tensorflow/core/util/sparse/ |
| D | sparse_tensor.h | 329 static inline int GetSliceIndex(const int dim, const int split_size, in GetSliceIndex() argument
332 DCHECK_GE(dim, 0); in GetSliceIndex()
333 if (residual == 0) return dim / split_size; in GetSliceIndex()
335 if (dim < offset) { in GetSliceIndex()
336 return dim / (split_size + 1); in GetSliceIndex()
338 return residual + ((dim - offset) / split_size); in GetSliceIndex()
343 static inline int GetDimensionInSlice(const int dim, const int split_size, in GetDimensionInSlice() argument
346 DCHECK_GE(dim, 0); in GetDimensionInSlice()
347 if (residual == 0) return dim % split_size; in GetDimensionInSlice()
349 if (dim < offset) { in GetDimensionInSlice()
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| /external/mesa3d/src/gallium/state_trackers/nine/ |
| D | nine_ff.h | 85 unsigned dim = context->ff.tex_stage[s][D3DTSS_TEXTURETRANSFORMFLAGS] & 0x7; in nine_ff_get_projected_key() local
89 if (dim > 4) in nine_ff_get_projected_key()
90 dim = input_texture_coord[s]; in nine_ff_get_projected_key()
92 if (!dim && gen == NINED3DTSS_TCI_PASSTHRU) in nine_ff_get_projected_key()
93 dim = input_texture_coord[s]; in nine_ff_get_projected_key()
94 else if (!dim) in nine_ff_get_projected_key()
95 dim = 4; in nine_ff_get_projected_key()
97 if (dim == 1) /* NV behaviour */ in nine_ff_get_projected_key()
99 if (dim > input_texture_coord[s] && gen == NINED3DTSS_TCI_PASSTHRU) in nine_ff_get_projected_key()
102 dim = 4; in nine_ff_get_projected_key()
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| /external/mesa3d/src/mesa/math/ |
| D | m_eval.c | 75 GLuint dim, GLuint order) in _math_horner_bezier_curve() argument
84 for (k = 0; k < dim; k++) in _math_horner_bezier_curve()
85 out[k] = s * cp[k] + bincoeff * t * cp[dim + k]; in _math_horner_bezier_curve()
87 for (i = 2, cp += 2 * dim, powert = t * t; i < order; in _math_horner_bezier_curve()
88 i++, powert *= t, cp += dim) { in _math_horner_bezier_curve()
92 for (k = 0; k < dim; k++) in _math_horner_bezier_curve()
98 for (k = 0; k < dim; k++) in _math_horner_bezier_curve()
119 GLuint dim, GLuint uorder, GLuint vorder) in _math_horner_bezier_surf() argument
121 GLfloat *cp = cn + uorder * vorder * dim; in _math_horner_bezier_surf()
122 GLuint i, uinc = vorder * dim; in _math_horner_bezier_surf()
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| /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
| D | rnn_cells_test.py | 34 self.dim = 10
38 expected_num_rows = 2 * self.dim
39 expected_num_cols = 4 * self.dim
42 random_ops.random_normal([self.batch_size, self.dim]))
44 random_ops.random_normal([self.batch_size, self.dim]))
46 random_ops.random_normal([self.batch_size, self.dim]))
48 lstm_cell = rnn_cells.MaskedBasicLSTMCell(self.dim)
62 expected_num_rows = 2 * self.dim
63 expected_num_cols = 4 * self.dim
66 random_ops.random_normal([self.batch_size, self.dim]))
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| /external/Microsoft-GSL/tests/ |
| D | strided_span_tests.cpp | 67 const multi_span<int, 5, 10> av = as_multi_span(multi_span<int>{data}, dim<5>(), dim<10>());
290 as_multi_span(multi_span<int>{data}, dim<5>(), dim<10>());
444 strided_span<int, 2> sav5{av.as_multi_span(dim<2>(), dim<2>()), {1}};
445 strided_span<int, 2> sav6{av.as_multi_span(dim<2>(), dim<2>()), {1, 1, 1}};
446 strided_span<int, 2> sav7{av.as_multi_span(dim<2>(), dim<2>()),
454 strided_span<int, 2> sav12{av.as_multi_span(dim<2>(), dim<2>()), {{1}, {1}}};
455 strided_span<int, 2> sav13{av.as_multi_span(dim<2>(), dim<2>()), {{1}, {1, 1, 1}}};
456 strided_span<int, 2> sav14{av.as_multi_span(dim<2>(), dim<2>()), {{1, 1, 1}, {1}}};
497 as_multi_span(bytes, dim<2>(), dim(bytes.size() / 2));
510 as_multi_span(bytes, dim<2>(), dim(bytes.size() / 2));
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