/external/tensorflow/tensorflow/python/kernel_tests/ |
D | broadcast_to_ops_test.py | 38 v_tf = array_ops.broadcast_to(constant_op.constant(x), [3, 3]) 39 v_np = np.broadcast_to(x, [3, 3]) 45 v_tf = array_ops.broadcast_to(constant_op.constant(x), [3, 3]) 46 v_np = np.broadcast_to(x, [3, 3]) 52 v_tf = array_ops.broadcast_to(constant_op.constant(x), [3, 3]) 53 v_np = np.broadcast_to(x, [3, 3]) 63 v_tf = array_ops.broadcast_to(constant_op.constant(x), output_shape) 64 v_np = np.broadcast_to(x, output_shape) 72 v_tf = array_ops.broadcast_to(constant_op.constant(x), output_shape) 73 v_np = np.broadcast_to(x, output_shape) [all …]
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D | batch_matmul_op_test.py | 259 array_ops.broadcast_to(matrix_a, broadcasted_a_shape), 260 array_ops.broadcast_to(matrix_b, broadcasted_b_shape)),
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_BroadcastTo.pbtxt | 32 >>> y = tf.broadcast_to(x, [3, 3]) 46 However, `broadcast_to` does not carry with it any such benefits. 48 shape. (In a graph context, `broadcast_to` might be fused to
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/external/tensorflow/tensorflow/python/ops/linalg/ |
D | linear_operator_tridiag.py | 320 rhs = array_ops.broadcast_to( 324 diagonals = array_ops.broadcast_to( 328 diagonals = array_ops.broadcast_to( 333 array_ops.broadcast_to(d, array_ops.concat( 348 return array_ops.broadcast_to(
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D | linear_operator_permutation.py | 223 x = array_ops.broadcast_to(x, broadcast_x_shape) 224 perm = array_ops.broadcast_to(perm, broadcast_shape)
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D | linear_operator_toeplitz.py | 254 row = array_ops.broadcast_to(row, total_shape) 255 col = array_ops.broadcast_to(col, total_shape)
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D | linear_operator_util.py | 348 batch_matrices[i] = array_ops.broadcast_to(mat, bcast_shape) 358 batch_matrices[i] = array_ops.broadcast_to(
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D | linalg_impl.py | 987 broadcast_rhs = array_ops.broadcast_to(rhs, rhs_broadcast_shape) 991 broadcast_perm = array_ops.broadcast_to(perm, rhs_broadcast_shape[:-1]) 994 broadcast_batch_indices = array_ops.broadcast_to( 1140 batch_indices = array_ops.broadcast_to(
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/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_where_op.py | 211 condition = ragged_tensor_shape.broadcast_to(condition, shape) 212 x = ragged_tensor_shape.broadcast_to(x, shape) 213 y = ragged_tensor_shape.broadcast_to(y, shape)
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D | ragged_batch_gather_with_default_op.py | 115 pad = ragged_tensor_shape.broadcast_to( 125 pad = array_ops.broadcast_to(default_value, pad_shape)
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D | ragged_tensor_shape.py | 476 def broadcast_to(rt_input, shape, broadcast_inner_dimensions=True): function 511 return array_ops.broadcast_to(rt_input, shape.inner_dim_sizes) 590 array_ops.broadcast_to(rt_input.flat_values, new_shape))
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D | ragged_dispatch.py | 220 x = ragged_tensor_shape.broadcast_to( 222 y = ragged_tensor_shape.broadcast_to(
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D | ragged_tensor_shape_test.py | 418 result = ragged_tensor_shape.broadcast_to(x, shape)
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/external/tensorflow/tensorflow/compiler/mlir/lite/tests/ |
D | legalize-tf.mlir | 1691 // CHECK: [[BCT:%.*]] = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<3xf32>, tensor<2xi32>) -> tenso… 1700 // CHECK: [[BCT:%.*]] = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<3xi32>, tensor<2xi32>) -> tenso… 1735 // CHECK: [[BCT:%.*]] = "tfl.broadcast_to"(%arg0, [[CST]]) 1736 // CHECK: [[BCT_0:%.*]] = "tfl.broadcast_to"(%arg1, [[CST]]) 1737 // CHECK: [[BCT_1:%.*]] = "tfl.broadcast_to"(%arg2, [[CST]]) 1749 // CHECK: [[BCT:%.*]] = "tfl.broadcast_to"(%arg1, [[CST]]) 1760 // CHECK: [[BCT:%.*]] = "tfl.broadcast_to"(%arg0, [[CST]]) 1761 // CHECK: [[BCT_0:%.*]] = "tfl.broadcast_to"(%arg1, [[CST]]) 1768 // CHECK: [[BCAST:%.*]] = "tfl.broadcast_to"(%arg0, [[CST]]) 1769 // CHECK: [[BCAST_1:%.*]] = "tfl.broadcast_to"(%arg1, [[CST]]) [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
D | linear_operator_permutation_test.py | 60 perm = array_ops.broadcast_to(perm, shape[:-1])
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/external/tensorflow/tensorflow/python/ops/linalg/sparse/ |
D | conjugate_gradient.py | 121 r0 = array_ops.broadcast_to(rhs, broadcast_rhs_shape)
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.distribute.-strategy-extended.pbtxt | 43 name: "broadcast_to"
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/external/tensorflow/tensorflow/python/data/experimental/benchmarks/ |
D | snapshot_dataset_benchmark.py | 50 lambda x: gen_array_ops.broadcast_to(x, [50, 50, 3]))
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/external/tensorflow/tensorflow/python/ops/numpy_ops/ |
D | np_array_ops.py | 138 return array_ops.broadcast_to(fill_value, shape) 156 return array_ops.broadcast_to(fill_value, array_ops.shape(a)) 1032 def broadcast_to(array, shape): # pylint: disable=redefined-outer-name function 1219 array_ops.broadcast_to(mask, array_ops.shape(m)), m, z) 1240 array_ops.broadcast_to(mask, array_ops.shape(m)), z, m) 1423 arr = array_ops.broadcast_to(arr, arr_shape) 1424 indices = array_ops.broadcast_to(indices, indices_shape) 1765 b = array_ops.broadcast_to(b, array_ops.shape(a))
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D | np_math_ops.py | 461 y = array_ops.broadcast_to(y, x.shape) 512 x1 = array_ops.broadcast_to(x1, shape) 513 x2 = array_ops.broadcast_to(x2, shape) 1287 weights_sum = np_array_ops.broadcast_to(weights_sum, array_ops.shape(avg))
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/external/tensorflow/tensorflow/compiler/tests/ |
D | binary_ops_test.py | 1349 np.broadcast_to(np.arange(0, 7, dtype=dtype), (3, 2, 1, 7)), 1356 expected=np.broadcast_to( 1365 np.broadcast_to( 1373 expected=np.broadcast_to( 1626 array_ops.broadcast_to, 1631 array_ops.broadcast_to, 1638 array_ops.broadcast_to, 1645 array_ops.broadcast_to,
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/external/tensorflow/tensorflow/lite/kernels/ |
D | Android.bp | 70 "broadcast_to.cc",
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/external/tensorflow/tensorflow/python/ops/parallel_for/ |
D | array_test.py | 146 return (array_ops.broadcast_to(x1, [2, 2, 3]), 147 array_ops.broadcast_to(x1, [1, 2, 1, 3]))
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/external/tensorflow/tensorflow/lite/ |
D | tflite_static.bp | 49 "kernels/broadcast_to.cc",
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/external/tensorflow/tensorflow/python/distribute/ |
D | values_util.py | 327 return strategy.extended.broadcast_to(
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