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Searched refs:block_rank (Results 1 – 9 of 9) sorted by relevance

/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dbatchtospace_op.cc31 const int block_rank = block_shape.size(); in BatchToSpace() local
34 ctx, input_rank >= 1 + block_rank, in BatchToSpace()
35 errors::InvalidArgument("input rank should be >= ", 1 + block_rank, in BatchToSpace()
38 remainder_shape.remove_prefix(1 + block_rank); in BatchToSpace()
43 block_rank == xla::ShapeUtil::GetDimension(crops.shape(), 0) && in BatchToSpace()
45 errors::InvalidArgument("crops should have shape [", block_rank, in BatchToSpace()
53 for (int i = 0; i < block_rank; ++i) { in BatchToSpace()
70 std::vector<int64> reshaped_shape(input_rank + block_rank); in BatchToSpace()
72 reshaped_shape[block_rank] = batch_size / block_num_elems; in BatchToSpace()
74 reshaped_shape.begin() + block_rank + 1); in BatchToSpace()
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Dspacetobatch_op.cc31 const int block_rank = block_shape.size(); in SpaceToBatch() local
34 ctx, input_rank >= 1 + block_rank, in SpaceToBatch()
35 errors::InvalidArgument("input rank should be >= ", 1 + block_rank, in SpaceToBatch()
38 remainder_shape.remove_prefix(1 + block_rank); in SpaceToBatch()
43 block_rank == xla::ShapeUtil::GetDimension(paddings.shape(), 0) && in SpaceToBatch()
45 errors::InvalidArgument("paddings should have shape [", block_rank, in SpaceToBatch()
57 for (int i = 0; i < block_rank; ++i) { in SpaceToBatch()
89 std::vector<int64> reshaped_padded_shape(input_rank + block_rank); in SpaceToBatch()
91 for (int i = 0; i < block_rank; ++i) { in SpaceToBatch()
102 reshaped_padded_shape.begin() + 1 + 2 * block_rank); in SpaceToBatch()
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/external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/
Dlower_tf.cc839 int64_t block_rank = block_shape_type.getNumElements(); in matchAndRewrite() local
840 int64_t remaining_rank = input_rank - 1 - block_rank; in matchAndRewrite()
879 for (uint64_t i = 0; i < block_rank; i++) { in matchAndRewrite()
889 for (int i = 0; i < block_rank; i++) { in matchAndRewrite()
931 block_rank, RankedTensorType::get({1}, rewriter.getIntegerType(64))); in matchAndRewrite()
940 for (int64_t i = 0; i < block_rank; ++i) { in matchAndRewrite()
959 for (int64_t i = 0; i < block_rank; ++i) { in matchAndRewrite()
966 for (int64_t i = 1 + block_rank; i < input_rank; ++i) { in matchAndRewrite()
979 for (int64_t i = 0; i < block_rank; ++i) { in matchAndRewrite()
983 for (int64_t i = 0; i < block_rank; ++i) { in matchAndRewrite()
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/external/tensorflow/tensorflow/compiler/mlir/tosa/transforms/
Dlegalize_common.cc826 int block_rank = block_shape[0]; in convertSpaceToBatchNDOp() local
829 int remaining_shape_rank = input_rank - block_rank - 1; in convertSpaceToBatchNDOp()
868 for (int i = 0; i < block_rank; i++) { in convertSpaceToBatchNDOp()
877 a0_pad_const[2 * (i + block_rank + 1) + 0] = 0; in convertSpaceToBatchNDOp()
878 a0_pad_const[2 * (i + block_rank + 1) + 1] = 0; in convertSpaceToBatchNDOp()
879 padded_shape[i + block_rank + 1] = input_shape[i + block_rank + 1]; in convertSpaceToBatchNDOp()
904 SmallVector<int64_t, 2> a2_shape(1 + block_rank * 2 + remaining_shape_rank); in convertSpaceToBatchNDOp()
908 for (int i = 0; i < block_rank; i++) { in convertSpaceToBatchNDOp()
921 a2_shape[1 + block_rank * 2 + i] = input_shape[1 + block_rank + i]; in convertSpaceToBatchNDOp()
942 for (int i = 0; i < block_rank; i++) { in convertSpaceToBatchNDOp()
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/external/tensorflow/tensorflow/lite/tools/
Dverifier.cc306 const int block_rank = total_dims - original_rank; in VerifyAndCountSparseElements() local
307 if (block_rank > 0) { in VerifyAndCountSparseElements()
312 if (sparse_rank != block_rank) { in VerifyAndCountSparseElements()
356 for (int i = 0; i < block_rank; i++) { in VerifyAndCountSparseElements()
/external/tensorflow/tensorflow/compiler/mlir/lite/transforms/
Ddense_to_sparse.cc66 int block_rank = 0; in PopulateEncodingParams() local
69 traversal_order->push_back(block_rank + dims_count); in PopulateEncodingParams()
71 block_rank++; in PopulateEncodingParams()
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/ir/
Dtf_ops_n_z.cc1226 const int64_t block_rank = in Verify() local
1230 if (block_rank == -1) { in Verify()
1235 if (input_type.hasRank() && input_type.getRank() < 1 + block_rank) { in Verify()
1258 for (uint64_t i = 0; i < block_rank; ++i) { in Verify()
1274 for (uint64_t i = 0; i < block_rank; ++i) { in Verify()
1318 const int64_t block_rank = in inferReturnTypes() local
1323 if (block_rank == ShapedType::kDynamicSize) { in inferReturnTypes()
1330 for (uint64_t i = 1 + block_rank; i < input_rank; ++i) { in inferReturnTypes()
1341 for (uint64_t i = 0; i < block_rank; ++i) { in inferReturnTypes()
Dtf_ops_a_m.cc428 const int block_rank = block_shape_ty.getShape().front(); in Verify() local
429 if (crops_ty.getRank() != 2 || crops_ty.getShape().front() != block_rank || in Verify()
431 op.emitOpError() << "crops should have shape [" << block_rank in Verify()
/external/tensorflow/tensorflow/compiler/mlir/tosa/g3doc/
Dlegalization.md714 size_t block_rank = %block.shape[0]
715 size_t remaining_shape_rank = %input.rank - block_rank - 1;
733 vector <size_t> a2_shape(1 + block_rank * 2 + remaining_shape_rank)
735 for (int i = 0; i < block_rank; i++) {
741 a2_shape[1 + block_rank * 2 + i] = %input.shape[1 + block_rank + i]
756 for (int i = 0; i < block_rank; i++) {
758 a3_perm[block_rank + 1 + i] = 2 * i + 1
762 a3_perm[block_rank] = 0
763 for (int i = (1 + block_rank * 2); i < %a2_reshape.rank; i++) {
779 for (int i = 0; i < block_rank; i++) {
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