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/external/tensorflow/tensorflow/compiler/xla/
Darray.h7 http://www.apache.org/licenses/LICENSE-2.0
20 #include <array>
46 // Performs a compile-time logical AND operation on the passed types (which
47 // must have `::value` members convertible to `bool`. Short-circuits if it
51 // This metafunction is designed to be a drop-in replacement for the C++17
68 // Compares three same-sized vectors elementwise. For each item in `values`,
69 // returns false if any of values[i] is outside the half-open range [starts[i],
84 // General N dimensional array class with arbitrary value type.
86 class Array {
90 // sees a single-element integer initializer. These typedefs allow casting
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Darray4d.h7 http://www.apache.org/licenses/LICENSE-2.0
31 #include "tensorflow/compiler/xla/array.h"
40 // Simple 4D array structure, similar in form to Array2D, for use primarily in
41 // testing and describing to XLA APIs values in the 4D array structures used
55 class Array4D : public Array<T> {
57 Array4D() : Array<T>(std::vector<int64>{0, 0, 0, 0}) {} in Array4D()
59 // Creates a 4D array, uninitialized values.
60 Array4D(int64 planes, int64 depth, int64 height, int64 width) in Array4D()
61 : Array<T>(std::vector<int64>{planes, depth, height, width}) {} in Array4D()
63 // Creates a 4D array, initialized to value.
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Darray2d.h7 http://www.apache.org/licenses/LICENSE-2.0
29 #include "tensorflow/compiler/xla/array.h"
39 class Array2D : public Array<T> {
41 Array2D() : Array<T>(std::vector<int64>{0, 0}) {} in Array2D()
43 Array2D(const int64 n1, const int64 n2) in Array2D()
44 : Array<T>(std::vector<int64>{n1, n2}) {} in Array2D()
46 Array2D(const int64 n1, const int64 n2, const T value) in Array2D()
47 : Array<T>({n1, n2}, value) {} in Array2D()
49 // Creates an array from the given nested initializer list. The outer
51 // For example, {{1, 2, 3}, {4, 5, 6}} results in an array with n1=2 and n2=3.
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Dreference_util.cc7 http://www.apache.org/licenses/LICENSE-2.0
18 #include <array>
39 for (int64 rowno = 0; rowno < input.height(); ++rowno) { in Array2DF32ToF64()
40 for (int64 colno = 0; colno < input.height(); ++colno) { in Array2DF32ToF64()
48 const Array3D<float>& lhs, const Array3D<float>& rhs, int64 kernel_stride, in ConvArray3D()
57 const Array3D<float>& lhs, const Array3D<float>& rhs, int64 kernel_stride, in ConvArray3DGeneralDimensionsDilated()
58 Padding padding, int64 lhs_dilation, int64 rhs_dilation, in ConvArray3DGeneralDimensionsDilated()
63 // Reuse the code for Array4D-convolution by extending the 3D input into a 4D in ConvArray3DGeneralDimensionsDilated()
64 // array by adding a fourth dummy dimension of size 1 without stride, padding in ConvArray3DGeneralDimensionsDilated()
67 a4dlhs.Each([&](absl::Span<const int64> indices, float* value_ptr) { in ConvArray3DGeneralDimensionsDilated()
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Dliteral.h7 http://www.apache.org/licenses/LICENSE-2.0
73 // Returns a Span of the array for this literal for the given NativeT
75 // ShapeIndex is not array. See primitive_util.h for the mapping from XLA type
81 // array at the given shape index. CHECKs if the subshape of the literal at
82 // the given ShapeIndex is not array.
84 int64 size_bytes(const ShapeIndex& shape_index = {}) const;
86 // Returns this literal's data as a string. This literal must be a rank-1 U8
87 // array.
93 // Warning: this function can take minutes for multi-million
98 // one-line form.
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Darray3d.h7 http://www.apache.org/licenses/LICENSE-2.0
27 #include "tensorflow/compiler/xla/array.h"
35 // Simple 3D array structure.
37 class Array3D : public Array<T> {
39 Array3D() : Array<T>(std::vector<int64>{0, 0, 0}) {} in Array3D()
41 // Creates an array of dimensions n1 x n2 x n3, uninitialized values.
42 Array3D(const int64 n1, const int64 n2, const int64 n3) in Array3D()
43 : Array<T>(std::vector<int64>{n1, n2, n3}) {} in Array3D()
45 // Creates an array of dimensions n1 x n2 x n3, initialized to value.
46 Array3D(const int64 n1, const int64 n2, const int64 n3, const T value) in Array3D()
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Darray_test.cc7 http://www.apache.org/licenses/LICENSE-2.0
16 #include "tensorflow/compiler/xla/array.h"
26 Array<int> uninit({2, 3}); in TEST()
34 Array<int> fullof7({1, 2, 3}, 7); 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()
50 Array<int> arr({{1, 2, 3}, {4, 5, 6}}); in TEST()
64 Array<Eigen::half> d2({{1.0f, 2.0f, 3.0f}, {4.0f, 5.0f, 6.0f}}); in TEST()
68 Array<Eigen::half> d3({{{1.0f}, {4.0f}}, {{1.0f}, {4.0f}}, {{1.0f}, {4.0f}}}); in TEST()
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Dreference_util.h7 http://www.apache.org/licenses/LICENSE-2.0
19 #include <array>
48 for (int64 w = 0; w < operand.width(); ++w) { in TransposeArray2D()
49 for (int64 h = 0; h < operand.height(); ++h) { in TransposeArray2D()
73 std::pair<int64, int64> kernel_stride, Padding padding);
79 std::pair<int64, int64> kernel_stride, Padding padding,
86 std::pair<int64, int64> kernel_stride, Padding padding,
87 std::pair<int64, int64> lhs_dilation,
88 std::pair<int64, int64> rhs_dilation, ConvolutionDimensionNumbers dnums);
95 int64 kernel_stride,
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/external/tensorflow/tensorflow/core/framework/
Dkernel_shape_util.cc7 http://www.apache.org/licenses/LICENSE-2.0
20 Status GetWindowedOutputSizeVerboseV2(int64 input_size, int64 filter_size, in GetWindowedOutputSizeVerboseV2()
21 int64 dilation_rate, int64 stride, in GetWindowedOutputSizeVerboseV2()
22 Padding padding_type, int64* output_size, in GetWindowedOutputSizeVerboseV2()
23 int64* padding_before, in GetWindowedOutputSizeVerboseV2()
24 int64* padding_after) { in GetWindowedOutputSizeVerboseV2()
34 int64 effective_filter_size = (filter_size - 1) * dilation_rate + 1; in GetWindowedOutputSizeVerboseV2()
37 *output_size = (input_size - effective_filter_size + stride) / stride; in GetWindowedOutputSizeVerboseV2()
41 *output_size = (input_size + *padding_before + *padding_after - in GetWindowedOutputSizeVerboseV2()
46 *output_size = (input_size + stride - 1) / stride; in GetWindowedOutputSizeVerboseV2()
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Dkernel_shape_util.h7 http://www.apache.org/licenses/LICENSE-2.0
19 #include <array>
45 // called instead. Note the padded area is zero-filled.
49 // - When Padding = SAME: the output size is (H'), where
53 // Pc = ((H' - 1) * S + K - H) / 2
55 // H' = H, Pc = (K-1)/2.
56 // This is where SAME comes from - the output has the same size as the input
59 // - When Padding = VALID: the output size is computed as
60 // H' = ceil(float(H - K + 1) / float(S))
63 // H' = H-K+1.
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/external/tensorflow/tensorflow/python/kernel_tests/
Dparse_single_example_op_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
53 return (np.empty(shape=(0, len(shape)), dtype=np.int64),
54 np.array([], dtype=dtype), np.array(shape, dtype=np.int64))
136 np.empty((0, 1), dtype=np.int64), # indices
137 np.empty((0,), dtype=np.int64), # sp_a is DT_INT64
138 np.array([0], dtype=np.int64)) # max_elems = 0
142 a_name: np.array([a_default]),
143 b_name: np.array(b_default),
144 c_name: np.array(c_default),
151 parsing_ops.VarLenFeature(dtypes.int64),
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Dsubstr_op_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
34 (np.int64, 1, "BYTE"),
35 (np.int32, -4, "BYTE"),
36 (np.int64, -4, "BYTE"),
38 (np.int64, 1, "UTF8_CHAR"),
39 (np.int32, -4, "UTF8_CHAR"),
40 (np.int64, -4, "UTF8_CHAR"),
45 "UTF8_CHAR": u"He\xc3\xc3\U0001f604".encode("utf-8"),
49 "UTF8_CHAR": u"e\xc3\xc3".encode("utf-8"),
51 position = np.array(pos, dtype)
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Dsparse_ops_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
34 import tensorflow.python.ops.sparse_grad # pylint: disable=unused-import
41 def _sparsify(x, thresh=0.5, index_dtype=np.int64):
56 ind = np.array([[0, 0], [1, 0], [1, 3], [1, 4], [3, 2], [3, 3]])
57 val = np.array([0, 10, 13, 14, 32, 33])
58 shape = np.array([5, 6])
60 constant_op.constant(ind, dtypes.int64),
62 constant_op.constant(shape, dtypes.int64))
66 ind = np.array([[0, 0, 1], [0, 1, 0], [0, 1, 2], [1, 0, 3], [1, 1, 0],
68 val = np.array([1, 10, 12, 103, 150, 149, 150, 122])
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Dparsing_ops_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
127 np.empty((0, 2), dtype=np.int64), # indices
128 np.empty((0,), dtype=np.int64), # sp_a is DT_INT64
129 np.array([2, 0], dtype=np.int64)) # batch == 2, max_elems = 0
133 a_name: np.array(2 * [[a_default]]),
134 b_name: np.array(2 * [b_default]),
135 c_name: np.array(2 * [c_default]),
144 parsing_ops.VarLenFeature(dtypes.int64),
147 (1, 3), dtypes.int64, default_value=a_default),
160 parsing_ops.VarLenFeature(dtypes.int64),
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/external/tensorflow/tensorflow/compiler/xla/service/
Dindexed_array_analysis.cc7 http://www.apache.org/licenses/LICENSE-2.0
40 string IndexedArrayAnalysis::ToString(Array* root, bool print_constants) { in ToString()
41 switch (root->kind()) { in ToString()
42 case Array::kUnknown: { in ToString()
43 auto* unknown_tensor = root->as<UnknownArray>(); in ToString()
44 return absl::StrCat("%", unknown_tensor->instruction().name()); in ToString()
47 case Array::kConstant: { in ToString()
49 string contents = root->as<ConstantArray>()->literal()->ToString(); in ToString()
50 return absl::StrCat("(constant ", ShapeUtil::HumanString(root->shape()), in ToString()
53 return absl::StrCat("(constant ", ShapeUtil::HumanString(root->shape()), in ToString()
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Dindexed_array_analysis.h7 http://www.apache.org/licenses/LICENSE-2.0
30 // gather from another array. It does this by mapping HLO instructions to
31 // instances of IndexedArrayAnalysis::Array, which can be inspected to discover
35 // IndexedArrayAnalysis maps each HLO instruction to an instance of a Array.
36 // Array really just a sum type of the classes that inherit from it. The
39 // Array instances are immutable once created.
40 class Array {
53 // Does a checked downcast from `Array` to `T` which must be one of its
57 static_assert((std::is_base_of<Array, T>::value), in as()
67 virtual ~Array() = default;
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Dhlo_sharding.h7 http://www.apache.org/licenses/LICENSE-2.0
27 #include "tensorflow/compiler/xla/array.h"
56 static HloSharding AssignDevice(int64 device_id,
61 static HloSharding Tile(const Array<int64>& tile_assignment,
71 const Array<int64>& group_tile_assignment,
72 absl::Span<const absl::Span<const int64>> replication_groups,
75 // Creates a partially replicated tiled sharding with device-level tile
79 const Array<int64>& tile_assignment_last_dim_replicate,
82 // Creates a new sharding which splits a one-dimensional input shape into
84 static HloSharding Tile1D(const Shape& input_shape, int64 num_tiles,
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/external/python/google-api-python-client/docs/dyn/
Dbigquery_v2.routines.html8 font-weight: inherit;
9 font-style: inherit;
10 font-size: 100%;
11 font-family: inherit;
12 vertical-align: baseline;
16 font-size: 13px;
21 font-size: 26px;
22 margin-bottom: 1em;
26 font-size: 24px;
27 margin-bottom: 1em;
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/external/tensorflow/tensorflow/compiler/tests/
Dbinary_ops_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
60 rtol = 1e-15 if a.dtype == np.float64 else 1e-3
62 atol = 1e-15 if a.dtype == np.float64 else 1e-6
79 a = -1.01
82 a = -1.001
87 np.array([[[[-1, 2.00009999], [-3, b]]]], dtype=dtype),
88 np.array([[[[a, 2], [-3.00009, 4]]]], dtype=dtype),
89 expected=np.array([[[[False, True], [True, False]]]], dtype=dtype))
93 np.array([3, 3, -1.5, -8, 44], dtype=dtype),
94 np.array([2, -2, 7, -4, 0], dtype=dtype),
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/external/libchrome/mojo/public/interfaces/bindings/tests/
Dtest_structs.mojom2 // Use of this source code is governed by a BSD-style license that can be
12 array<Rect>? rects;
39 int64 f7;
55 array<string> f23;
56 array<string?> f24;
57 array<string>? f25;
58 array<string?>? f26;
76 int64 f7 = 100;
124 map<int64, int64> f7;
137 map<string, array<string>> f0;
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/external/tensorflow/tensorflow/core/kernels/
Dpooling_ops_3d.cc7 http://www.apache.org/licenses/LICENSE-2.0
19 #include <array>
55 errors::InvalidArgument("tensor_in must be 4-dimensional")); in Pool3dParameters()
57 this->data_format = data_format; in Pool3dParameters()
98 const std::array<int64, 3>& window, in launch()
99 const std::array<int64, 3>& stride, in launch()
100 const std::array<int64, 3>& padding, in launch()
103 output->tensor<T, 5>().device(context->eigen_device<CPUDevice>()) = in launch()
113 const std::array<int64, 3>& window, in launch()
114 const std::array<int64, 3>& stride, in launch()
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Drandom_op_gpu.h7 http://www.apache.org/licenses/LICENSE-2.0
38 random::PhiloxRandom gen, T* data, int64 size,
47 int64 size, Distribution dist);
55 const tensorflow::random::Array<T, ElementCount>& array) const {
58 buf[i] = array[i];
66 // Copies the elements from the array to buf. buf must be 128-bit aligned,
71 const tensorflow::random::Array<float, 4>& array) const {
72 // NOTE(ringwalt): It's not safe to cast &array[0] to a float4, because they
73 // have 32-bit alignment vs 128-bit alignment. There seems to be no
76 vec.x = array[0];
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/external/tensorflow/tensorflow/python/keras/layers/preprocessing/
Dinteger_lookup_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
60 # Create an array where 1138 is the most frequent term, followed by
64 np.array([[42], [1138], [1138], [1138], [1138], [1729], [1729],
66 dtype=np.int64),
68 np.array([[1138], [1729], [725], [42], [42], [725], [1138], [4]],
69 dtype=np.int64),
72 "dtype": dtypes.int64,
76 dtypes.int64
101 expected_output_dtype = dtypes.int64
108 # together. When the results have different shapes on the non-concat
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Dtable_utils_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
41 value_dtype=dtypes.int64,
42 default_value=-7,
68 dtypes.int64,
72 table = lookup_ops.StaticHashTable(init, default_value=-7)
74 table = lookup_ops.StaticHashTableV1(init, default_value=-7)
108 vocab_data = np.array([10, 11, 12, 13], dtype=np.int64)
111 values=np.array([13, 32], dtype=np.int64),
118 table = get_table(dtype=dtypes.int64, oov_tokens=[1])
139 vocab_data = np.array([10, 11, 12, 13], dtype=np.int64)
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Dindex_lookup_test.py7 # http://www.apache.org/licenses/LICENSE-2.0
62 # Create an array where 'earth' is the most frequent term, followed by
66 np.array([["fire"], ["earth"], ["earth"], ["earth"], ["earth"],
69 np.array([["earth"], ["wind"], ["and"], ["fire"], ["fire"],
85 # Create an array where 'earth' is the most frequent term, followed by
89 np.array([["fire"], ["earth"], ["earth"], ["earth"], ["earth"],
92 np.array([[1], [2], [3], [4], [4], [3], [1], [5]]),
102 np.array([[b"earth"], [b"wind"], [b"and"], [b"fire"], [b"fire"],
105 dtypes.int64
113 np.array([["fire"], ["earth"], ["earth"], ["earth"], ["earth"],
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