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/external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/
Dnot_supported.txt9 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf…
10 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf…
11 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.i…
12 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.i…
13 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf…
14 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf…
15 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.i…
16 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.i…
17 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.i…
18 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.i…
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Dtest_manifest.txt17 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[…
18 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[…
19 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='SAME',strides=[…
20 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides…
21 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides…
22 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,15,14,1],ksize=[1,1,1,1],padding='SAME',strides…
23 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides…
24 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides…
25 avg_pool/avg_pool_data_format='NHWC',input_shape=[3,15,14,3],ksize=[1,1,1,1],padding='SAME',strides…
26 avg_pool/avg_pool_data_format='NHWC',input_shape=[1,1,1,1],ksize=[1,1,1,1],padding='VALID',strides=…
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/external/tensorflow/tensorflow/python/keras/applications/
Dimagenet_utils.py245 def obtain_input_shape(input_shape, argument
271 if weights != 'imagenet' and input_shape and len(input_shape) == 3:
273 if input_shape[0] not in {1, 3}:
276 str(input_shape[0]) + ' input channels.')
277 default_shape = (input_shape[0], default_size, default_size)
279 if input_shape[-1] not in {1, 3}:
282 str(input_shape[-1]) + ' input channels.')
283 default_shape = (default_size, default_size, input_shape[-1])
290 if input_shape is not None:
291 if input_shape != default_shape:
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Defficientnet.py156 input_shape=None, argument
222 input_shape = imagenet_utils.obtain_input_shape(
223 input_shape,
231 img_input = layers.Input(shape=input_shape)
234 img_input = layers.Input(tensor=input_tensor, shape=input_shape)
460 input_shape=None, argument
473 input_shape=input_shape,
484 input_shape=None, argument
497 input_shape=input_shape,
508 input_shape=None, argument
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/external/tensorflow/tensorflow/python/keras/utils/
Dconv_utils_test.py30 def _get_const_output_shape(input_shape, dim): argument
31 return tuple([min(d, dim) for d in input_shape])
166 def test_conv_kernel_mask_fc(self, *input_shape): argument
168 kernel_shape = input_shape
169 ndims = len(input_shape)
171 output_shape = _get_const_output_shape(input_shape, dim=1)
172 mask = np.ones(input_shape + output_shape, np.bool)
176 input_shape,
183 def test_conv_kernel_mask_diag(self, *input_shape): argument
184 ndims = len(input_shape)
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/external/tensorflow/tensorflow/lite/kernels/internal/
Dtranspose_utils_test.cc24 RuntimeShape input_shape({9}); in TEST() local
31 transpose_utils::RemoveOneSizeDimensions(&input_shape, &output_shape, in TEST()
34 EXPECT_EQ(input_shape, RuntimeShape({9})); in TEST()
42 RuntimeShape input_shape({9, 3}); in TEST() local
50 transpose_utils::RemoveOneSizeDimensions(&input_shape, &output_shape, in TEST()
53 EXPECT_EQ(input_shape, RuntimeShape({9, 3})); in TEST()
62 RuntimeShape input_shape({9, 1}); in TEST() local
70 transpose_utils::RemoveOneSizeDimensions(&input_shape, &output_shape, in TEST()
73 EXPECT_EQ(input_shape, RuntimeShape({9})); in TEST()
81 RuntimeShape input_shape({4, 3, 8}); in TEST() local
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Dtranspose_utils.cc21 const RuntimeShape& input_shape, int* dim0, in IsTranspose2DApplicable() argument
23 const int dims_cnt = input_shape.DimensionsCount(); in IsTranspose2DApplicable()
26 *dim0 = input_shape.Dims(0); in IsTranspose2DApplicable()
27 *dim1 = input_shape.Dims(1); in IsTranspose2DApplicable()
45 *dim0 *= input_shape.Dims(i); in IsTranspose2DApplicable()
47 *dim1 *= input_shape.Dims(i); in IsTranspose2DApplicable()
53 void RemoveOneSizeDimensions(RuntimeShape* input_shape, in RemoveOneSizeDimensions() argument
56 const int dims_cnt = input_shape->DimensionsCount(); in RemoveOneSizeDimensions()
61 if (input_shape->Dims(i) == 1) { in RemoveOneSizeDimensions()
71 if (input_shape->FlatSize() == 1) { in RemoveOneSizeDimensions()
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Dresize_nearest_neighbor_test.cc30 const RuntimeShape& input_shape, const std::vector<T>& input_data, in TestReferenceResizeNearestNeighbor() argument
39 op_params, input_shape, input_data.data(), output_size_shape, in TestReferenceResizeNearestNeighbor()
48 RuntimeShape input_shape = {1, 2, 2, 1}; in TEST() local
54 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data, in TEST()
59 RuntimeShape input_shape = {1, 2, 2, 1}; in TEST() local
65 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data, in TEST()
70 RuntimeShape input_shape = {1, 3, 3, 1}; in TEST() local
76 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data, in TEST()
81 RuntimeShape input_shape = {1, 2, 2, 1}; in TEST() local
87 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data, in TEST()
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/external/tensorflow/tensorflow/python/kernel_tests/
Dpool_test.py148 def _test(self, input_shape, **kwargs): argument
152 np.prod(input_shape), dtype=np.float32).reshape(input_shape) - 1
162 input_shape=[1, 1, 10, 1],
173 for input_shape in [[2, 9, 2], [2, 10, 2]]:
178 input_shape=input_shape,
188 input_shape=input_shape,
199 for input_shape in [[2, 9, 10, 2], [2, 10, 9, 2]]:
204 input_shape=input_shape,
214 input_shape=input_shape,
227 for input_shape in [[2, 9, 10, 11, 2], [2, 10, 9, 11, 2]]:
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dsplit_op.cc39 const TensorShape input_shape = ctx->InputShape(1); in Compile() local
48 int32 split_dim = split_dim_orig < 0 ? split_dim_orig + input_shape.dims() in Compile()
50 OP_REQUIRES(ctx, 0 <= split_dim && split_dim < input_shape.dims(), in Compile()
51 errors::InvalidArgument("-input rank(-", input_shape.dims(), in Compile()
53 input_shape.dims(), "), but got ", in Compile()
62 ctx, input_shape.dim_size(split_dim) % num_split == 0, in Compile()
66 split_dim_orig, " (size = ", input_shape.dim_size(split_dim), ") ", in Compile()
71 const int32 slice_size = input_shape.dim_size(split_dim) / num_split; in Compile()
75 std::vector<int64> begin(input_shape.dims(), 0); in Compile()
76 std::vector<int64> limits(input_shape.dims()); in Compile()
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Dunpack_op.cc47 const TensorShape input_shape = ctx->InputShape(0); in Compile() local
50 if (axis < 0) axis += input_shape.dims(); in Compile()
52 OP_REQUIRES(ctx, 0 <= axis && axis < input_shape.dims(), in Compile()
54 -input_shape.dims(), ", ", in Compile()
55 input_shape.dims(), ")")); in Compile()
58 ctx, input_shape.dims() > 0 && input_shape.dim_size(axis) == num, in Compile()
60 ", got shape ", input_shape.DebugString())); in Compile()
62 auto output_shape = input_shape; in Compile()
67 std::vector<int64> start_indices(input_shape.dims(), 0); in Compile()
68 std::vector<int64> limit_indices(input_shape.dims()); in Compile()
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Dshape_op.cc42 const TensorShape input_shape = ctx->InputShape(0); in Compile() local
44 const int rank = input_shape.dims(); in Compile()
56 Tensor shape_constant(out_dtype_, TensorShape({input_shape.dims()})); in Compile()
57 OP_REQUIRES_OK(ctx, TensorShapeToConstant(input_shape, &shape_constant)); in Compile()
76 const TensorShape input_shape = ctx->InputShape(i); in Compile() local
79 const int rank = input_shape.dims(); in Compile()
93 Tensor shape_constant(out_dtype_, TensorShape({input_shape.dims()})); in Compile()
95 TensorShapeToConstant(input_shape, &shape_constant)); in Compile()
113 const TensorShape input_shape = ctx->InputShape(0); in Compile() local
114 const int rank = input_shape.dims(); in Compile()
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Dspacetodepth_op.cc60 absl::Span<const int64> input_shape = in Compile() local
62 int input_rank = input_shape.size(); in Compile()
81 OP_REQUIRES(ctx, input_shape[1 + i] % block_size_ == 0, in Compile()
83 "input shape[", 1 + i, "]=", input_shape[1 + i], in Compile()
88 reshaped_shape.push_back(input_shape[0]); in Compile()
90 reshaped_shape.push_back(input_shape[1 + i] / block_size_); in Compile()
93 reshaped_shape.push_back(input_shape[feature_dim]); in Compile()
104 output_shape.push_back(input_shape[0]); in Compile()
106 output_shape.push_back(input_shape[1 + i] / block_size_); in Compile()
108 output_shape.push_back(input_shape[feature_dim] * block_elems); in Compile()
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Ddepthtospace_op.cc60 absl::Span<const int64> input_shape = in Compile() local
62 int input_rank = input_shape.size(); in Compile()
79 reshaped_shape.push_back(input_shape[0]); in Compile()
81 reshaped_shape.push_back(input_shape[1 + i]); in Compile()
88 reshaped_shape.push_back(input_shape[feature_dim] / block_elems); in Compile()
97 output_shape.push_back(input_shape[0]); in Compile()
99 output_shape.push_back(input_shape[1 + i] * block_size_); in Compile()
101 output_shape.push_back(input_shape[feature_dim] / block_elems); in Compile()
104 reshaped_shape.push_back(input_shape[0]); in Compile()
110 reshaped_shape.push_back(input_shape[feature_dim] / block_elems); in Compile()
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Dslice_op.cc40 const TensorShape input_shape = ctx->InputShape(0); in Compile() local
48 begin_tensor_shape.num_elements() == input_shape.dims() && in Compile()
49 size_tensor_shape.num_elements() == input_shape.dims(), in Compile()
52 input_shape.dims(), ", but got shapes ", in Compile()
56 const int input_dims = input_shape.dims(); in Compile()
66 size[i] = input_shape.dim_size(i) - begin[i]; in Compile()
73 if (input_shape.dim_size(i) == 0) { in Compile()
80 OP_REQUIRES(ctx, 0 <= b && b <= input_shape.dim_size(i), in Compile()
82 input_shape.dim_size(i), in Compile()
84 OP_REQUIRES(ctx, 0 <= s && b + s <= input_shape.dim_size(i), in Compile()
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/external/tensorflow/tensorflow/python/keras/layers/
Dpooling.py83 def compute_output_shape(self, input_shape): argument
84 input_shape = tensor_shape.TensorShape(input_shape).as_list()
86 steps = input_shape[2]
87 features = input_shape[1]
89 steps = input_shape[1]
90 features = input_shape[2]
96 return tensor_shape.TensorShape([input_shape[0], features, length])
98 return tensor_shape.TensorShape([input_shape[0], length, features])
299 def compute_output_shape(self, input_shape): argument
300 input_shape = tensor_shape.TensorShape(input_shape).as_list()
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Dconvolutional.py149 def build(self, input_shape): argument
150 input_shape = tensor_shape.TensorShape(input_shape)
151 input_channel = self._get_input_channel(input_shape)
177 self._build_conv_op_input_shape = input_shape
183 input_shape,
222 def compute_output_shape(self, input_shape): argument
223 input_shape = tensor_shape.TensorShape(input_shape).as_list()
225 space = input_shape[1:-1]
235 return tensor_shape.TensorShape([input_shape[0]] + new_space +
238 space = input_shape[2:]
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Dcore.py117 def compute_output_shape(self, input_shape): argument
118 return input_shape
186 def compute_output_shape(self, input_shape): argument
187 return input_shape
236 input_shape = array_ops.shape(inputs)
237 noise_shape = (input_shape[0], 1, input_shape[2])
293 input_shape = array_ops.shape(inputs)
295 return (input_shape[0], input_shape[1], 1, 1)
297 return (input_shape[0], 1, 1, input_shape[3])
351 input_shape = array_ops.shape(inputs)
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Dpooling_test.py37 input_shape=(3, 4, 5))
40 input_shape=(3, 4, 5))
42 keras.layers.pooling.GlobalAveragePooling1D, input_shape=(3, 4, 5))
45 input_shape=(3, 4, 5))
50 model.add(keras.layers.Masking(mask_value=0., input_shape=(None, 4)))
72 masking = keras.layers.Masking(mask_value=0., input_shape=(3, 2))(inputs)
118 input_shape=(3, 4, 5, 6))
122 input_shape=(3, 5, 6, 4))
126 input_shape=(3, 4, 5, 6))
130 input_shape=(3, 5, 6, 4))
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Dmerge.py90 def build(self, input_shape): argument
92 if not isinstance(input_shape, list):
94 if len(input_shape) < 2:
97 'Got ' + str(len(input_shape)) + ' inputs.')
98 batch_sizes = {s[0] for s in input_shape if s is not None} - {None}
102 'batch sizes. Got tensors with shapes : ' + str(input_shape))
103 if input_shape[0] is None:
106 output_shape = input_shape[0][1:]
107 for i in range(1, len(input_shape)):
108 if input_shape[i] is None:
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Dkernelized.py156 def build(self, input_shape): argument
157 input_shape = tensor_shape.TensorShape(input_shape)
160 if input_shape.rank != 2:
163 input_shape.ndims))
164 if input_shape.dims[1].value is None:
169 ndim=2, axes={1: input_shape.dims[1].value})
170 input_dim = input_shape.dims[1].value
200 super(RandomFourierFeatures, self).build(input_shape)
209 def compute_output_shape(self, input_shape): argument
210 input_shape = tensor_shape.TensorShape(input_shape)
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/
Dpooling.h27 const RuntimeShape& input_shape, in AveragePool() argument
30 TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4); in AveragePool()
32 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in AveragePool()
33 const int depth = MatchingDim(input_shape, 3, output_shape, 3); in AveragePool()
34 const int input_height = input_shape.Dims(1); in AveragePool()
35 const int input_width = input_shape.Dims(2); in AveragePool()
65 input_data[Offset(input_shape, batch, in_y, in_x, channel)]; in AveragePool()
80 const RuntimeShape& input_shape, in AveragePool() argument
85 TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4); in AveragePool()
87 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in AveragePool()
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/external/tensorflow/tensorflow/python/ops/
Dconcat_benchmark.py35 def build_graph(device, input_shape, variable, num_inputs, axis, grad): argument
51 inputs = [array_ops.zeros(input_shape) for _ in range(num_inputs)]
56 input_shape[0],
57 random.randint(max(1, input_shape[1] - 5), input_shape[1] + 5)
63 random.randint(max(1, input_shape[0] - 5), input_shape[0] + 5),
64 input_shape[1]
81 def _run_graph(self, device, input_shape, variable, num_inputs, axis, grad, argument
99 outputs = build_graph(device, input_shape, variable, num_inputs, axis,
112 "GB/sec" % (device, input_shape[0], input_shape[1], variable,
114 num_inputs * input_shape[0] * input_shape[1] * 4 * 2 *
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/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_BatchToSpaceND.pbtxt6 N-D with shape `input_shape = [batch] + spatial_shape + remaining_shape`,
23 `crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]`.
30 input_shape[1], ..., input_shape[N-1]]
35 input_shape[1], block_shape[0],
37 input_shape[M], block_shape[M-1],
39 input_shape[M+1], ..., input_shape[N-1]]
44 input_shape[1] * block_shape[0],
46 input_shape[M] * block_shape[M-1],
48 input_shape[M+1],
50 input_shape[N-1]]
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/external/tensorflow/tensorflow/lite/kernels/internal/optimized/
Dim2col_utils.h25 inline void ExtractPatchIntoBufferColumn(const RuntimeShape& input_shape, int w, in ExtractPatchIntoBufferColumn() argument
34 TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4); in ExtractPatchIntoBufferColumn()
56 int in_offset = Offset(input_shape, b, ih_start, iw_start, 0); in ExtractPatchIntoBufferColumn()
116 const RuntimeShape& input_shape, const T* input_data, in DilatedIm2col() argument
125 TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4); in DilatedIm2col()
135 const int batches = MatchingDim(input_shape, 0, output_shape, 0); in DilatedIm2col()
136 const int input_height = input_shape.Dims(1); in DilatedIm2col()
137 const int input_width = input_shape.Dims(2); in DilatedIm2col()
138 const int input_depth = MatchingDim(input_shape, 3, filter_shape, 3); in DilatedIm2col()
177 input_data + Offset(input_shape, batch, in_y, in_x, 0); in DilatedIm2col()
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