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Results 1 - 8 of 8 for ranked_type (0.24 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/tpu_space_to_depth_pass.cc
// Handles padding before convolution for space to depth transform. LogicalResult HandlePad(TF::PadOp op, int32_t kernel_size, int32_t block_size) { auto ranked_type = mlir::dyn_cast<RankedTensorType>(op.getInput().getType()); if (!ranked_type) return failure(); auto pad_input_shape = ranked_type.getShape(); Location loc = op.getLoc(); OpBuilder builder(op); builder.setInsertionPoint(op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 29.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/functional_control_flow_to_regions.cc
} // Converts the condition for an IfOp/WhileOp to a boolean value. Value ConvertConditionToBoolean(Operation* op, Value cond) { if (auto ranked_type = mlir::dyn_cast<RankedTensorType>(cond.getType())) if (ranked_type.getRank() == 0 && ranked_type.getElementType().isSignlessInteger(1)) return cond; OpBuilder builder(op); Value to_bool = builder.create<TF::ToBoolOp>(op->getLoc(), cond);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/xla_broadcast.cc
elem_type.isF32()) { zero = builder.getFloatAttr(elem_type, 0); } else { return false; } if (auto ranked_type = dyn_cast<RankedTensorType>(type)) { llvm::ArrayRef<int64_t> type_shape = ranked_type.getShape(); for (int64_t i : type_shape) { if (i < 0) return false; } shape = builder.getI64TensorAttr(type_shape); } else { return false;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 13 18:52:07 UTC 2024 - 13.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/tpu_sharding_identification_pass.cc
// verify shardings that actually break a tensor apart. return mlir::success(); } if (RankedTensorType ranked_type = mlir::dyn_cast<RankedTensorType>(type)) { const int64_t tensor_rank = ranked_type.getRank(); int tile_assignment_rank = sharding->tile_assignment_dimensions_size(); // When a tensor is partial or subgroup tiled, its tile assignment will
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 02:01:13 UTC 2024 - 28.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/tf2xla_rewriter.cc
bool IsBounded(Type ty) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); if (!ranked_ty) return false; if (ranked_ty.hasStaticShape()) return true; auto encoding = mlir::dyn_cast_or_null<TypeExtensionsAttr>(ranked_ty.getEncoding()); if (!encoding) return false; for (int i = 0; i < ranked_ty.getRank(); ++i) { if (ranked_ty.isDynamicDim(i) &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:16:07 UTC 2024 - 18.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
} // Combine the result of each individual MatMul into a rank-3 tensor. Type packed_type = RankedTensorType::get( {bcast.output_batch_size(), rows, cols}, element_type); const auto axis = rewriter.getI64IntegerAttr(0); auto pack_op = rewriter.create<TF::PackOp>(loc, packed_type, /*values=*/matmuls, axis); // Reshape the rank-3 tensor into the correct output shape.
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/quantization/tensorflow/fallback_to_flex_ops.cc
return f.isExactlyValue(value); }); } // Returns true if the rank of the value equals to the given rank. bool RankEquals(Value value, int rank) { auto rank_type = mlir::dyn_cast<RankedTensorType>(value.getType()); return (rank_type && rank_type.getRank() == rank); } #include "tensorflow/compiler/mlir/lite/quantization/tensorflow/fallback_to_flex_patterns.inc" void FallbackToFlexOps::runOnOperation() {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
// neither. mlir::RankedTensorType GetBufferType(mlir::Type ty) { auto ranked_ty = mlir::dyn_cast_or_null<mlir::RankedTensorType>(ty); if (!ranked_ty) return {}; int64_t rank = ranked_ty.getRank(); llvm::SmallVector<int64_t, 4> dims = llvm::to_vector<4>(ranked_ty.getShape()); auto encoding = mlir::dyn_cast_or_null<mlir::mhlo::TypeExtensionsAttr>( ranked_ty.getEncoding()); if (encoding && !encoding.getBounds().empty()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 45.3K bytes - Viewed (0)