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Results 1 - 10 of 45 for getShape (0.19 sec)
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tensorflow/compiler/mlir/lite/utils/utils.h
if (!shaped_type || !shaped_type.hasStaticShape()) { return false; } if (operand_num == 0) { shape = shaped_type.getShape(); } else { if (shape != shaped_type.getShape()) { return false; } } ++operand_num; } return true; } // Utility function to map final permutation to initial permutation
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
dot_dimension_numbers.ParseFromString(dot_dimension_numbers_str.str()); SmallVector<Value> input_arguments = {lhs, rhs}; const int lhs_rank = mlir::cast<ShapedType>(lhs.getType()).getShape().size(); const int rhs_rank = mlir::cast<ShapedType>(rhs.getType()).getShape().size(); const std::string einsum_equation = CreateEinsumEquation(dot_dimension_numbers, lhs_rank, rhs_rank);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
mlir::cast<ShapedType>(lhs.getType()).getShape(), mlir::cast<ShapedType>(rhs.getType()).getShape(), symbolic_broadcast_shape)) { return failure(); } // Calculates the broadcast shape using BroadcastArgs op. Value lhs_shape = GetShape(lhs, op->getLoc(), rewriter); Value rhs_shape = GetShape(rhs, op->getLoc(), rewriter); auto broadcast_shape =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/collection_ops_util.cc
Location loc) { auto buffer_type = mlir::cast<RankedTensorType>(buffer.getType()); if (buffer_type.getShape().size() == 1) return index; // Create a concat of index and trailing zeros. llvm::SmallVector<int64_t, 8> zeros(buffer_type.getShape().size() - 1, 0); auto zeros_tensor = GetR1Const(zeros, builder, loc); return builder.create<TF::ConcatV2Op>( loc,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/optimize.cc
// Extract Z from %dot. ArrayRef<int64_t> shape_z = dot.getType().getShape().drop_front(shape_b.size() + shape_y2.size()); // Check %after shape. if (reshape_after.getType().getShape() != ArrayRef<int64_t>(llvm::to_vector( llvm::concat<const int64_t>(shape_b, shape_y1, shape_z)))) { return failure(); } rewriter.replaceOpWithNewOp<mhlo::DotGeneralOp>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 26.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
RankedTensorType tensorType = mlir::cast<RankedTensorType>(value.getType()); Type element_type = tensorType.getElementType(); int rank = tensorType.getShape().size(); int num_rows = tensorType.getShape()[rank - 2]; int num_cols = tensorType.getShape()[rank - 1]; std::vector<Value> sliced; if (batch_size == 1) { // Batch size is 1, no splitting is required
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.cc
auto x_type = mlir::dyn_cast<RankedTensorType>(x.getType()); auto y_type = mlir::dyn_cast<RankedTensorType>(y.getType()); if (!x_type || !y_type) return failure(); if (x_type.getShape() != y_type.getShape()) return failure(); auto result_type = squared_diff_op.getType(); if (!result_type) return failure(); auto sub_op = rewriter.create<TF::SubOp>(squared_diff_op.getLoc(), result_type, x, y);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 25.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/util.cc
ConversionPatternRewriter& rewriter) { if (index_vector_dim == indices_type.getRank()) { llvm::SmallVector<int64_t, 4> new_start_indices_shape( indices_type.getShape().begin(), indices_type.getShape().end()); new_start_indices_shape.push_back(1); indices_type = RankedTensorType::get(new_start_indices_shape, indices_type.getElementType());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils_test.cc
auto output_types = fused_lstm_func_.getFunctionType().getResults(); SmallVector<int64_t, 2> output_shape{1, mlir::ShapedType::kDynamic}; EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getShape().size(), output_shape.size()); for (int i = 0; i < output_shape.size(); i++) { EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getDimSize(i), output_shape[i]); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_xla_attribute_utils.cc
Value temp_padding = CreateConstValue<int32_t>(builder, loc, {num_dims, 2}, padding_values); SmallVector<int64_t> output_shape(input_shape.getShape().begin(), input_shape.getShape().end()); for (int i : spatial_dims) { output_shape[i] += padding_values[2 * i] + padding_values[2 * i + 1]; } return builder.create<TF::PadV2Op>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0)