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llvm · Aug 15, 2022 · 5906761 · 5906761
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commit 5906761
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Showing 4 changed files with 7 additions and 17 deletions.
diff --git a/lib/Conversion/TorchToLinalg/Linear.cpp b/lib/Conversion/TorchToLinalg/Linear.cpp
@@ -7,7 +7,6 @@
 //
 //===----------------------------------------------------------------------===//
 
-#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
 #include "torch-mlir/Conversion/TorchToLinalg/TorchToLinalg.h"
 
 #include "../PassDetail.h"
@@ -21,12 +20,9 @@
 #include "torch-mlir/Conversion/Utils/Utils.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchDialect.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
-#include "torch-mlir/Dialect/Torch/IR/TorchTypes.h"
 #include "torch-mlir/Dialect/Torch/Utils/TorchUpstream.h"
 #include "torch-mlir/Dialect/Torch/Utils/Utils.h"
-#include "llvm/ADT/ArrayRef.h"
 #include <algorithm>
-#include <bits/stdint-intn.h>
 
 using namespace mlir;
 using namespace mlir::torch;
@@ -776,7 +772,6 @@ class ConvertAtenConvolutionOp : public OpConversionPattern<AtenConvolutionOp> {
         Value outerSize = rewriter.create<arith::MulIOp>(loc, offset, c2);
         outerSize = rewriter.create<arith::AddIOp>(loc, outerSize, innerSize);
 
-        innerSizes.push_back(innerSize);
         outerSizes.push_back(outerSize);
         offsets.push_back(offset);
       }
@@ -792,8 +787,8 @@ class ConvertAtenConvolutionOp : public OpConversionPattern<AtenConvolutionOp> {
       SmallVector<Value> insertSizes = getTensorSizes(rewriter, loc, input);
 
       paddedInput = rewriter.create<tensor::InsertSliceOp>(
-          loc, torch_to_linalg::dynamicCast(rewriter, loc, input), initTensor,
-          offsets, insertSizes, strideIndexValues);
+          loc, torch_to_linalg::removeSizeInformation(rewriter, loc, input),
+          initTensor, offsets, insertSizes, strideIndexValues);
 
       // Calculate output dims
       for (size_t i = 0; i < numSpacialDims; i++)
@@ -804,11 +799,7 @@ class ConvertAtenConvolutionOp : public OpConversionPattern<AtenConvolutionOp> {
       // Set stride to 1
       strideInts.clear();
       strideInts.append(numSpacialDims, 1);
-      strideIntValues = getAsConstantIntValues(rewriter, loc, strideInts);
 
-      paddingIntValues.clear();
-      for (auto pad = offsets.begin() + 2; pad < offsets.end(); pad++)
-        paddingIntValues.push_back(castIndexToInt(*pad));
     } else {
       // Pad input
       SmallVector<int64_t, 4> paddingIncludingNC = {0, 0};

diff --git a/lib/Conversion/TorchToLinalg/Utils.cpp b/lib/Conversion/TorchToLinalg/Utils.cpp
@@ -20,7 +20,6 @@
 #include "torch-mlir/Conversion/Utils/Utils.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchDialect.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
-#include "torch-mlir/Dialect/Torch/IR/TorchTypes.h"
 #include "torch-mlir/Dialect/Torch/Utils/TorchUpstream.h"
 #include "torch-mlir/Dialect/Torch/Utils/Utils.h"
 
@@ -365,7 +364,8 @@ LogicalResult torch_to_linalg::broadcastToGivenShape(
   return success();
 }
 
-Value torch_to_linalg::dynamicCast(OpBuilder &b, Location loc, Value tensor) {
+Value torch_to_linalg::removeSizeInformation(OpBuilder &b, Location loc,
+                                             Value tensor) {
   auto tensorType = tensor.getType().cast<RankedTensorType>();
   auto rank = tensorType.getRank();
   SmallVector<int64_t> unknownSizes(rank, kUnknownSize);

diff --git a/lib/Conversion/TorchToLinalg/Utils.h b/lib/Conversion/TorchToLinalg/Utils.h
@@ -71,8 +71,7 @@ LogicalResult broadcastToGivenShape(Operation *op, PatternRewriter &rewriter,
 
 // Cast a tensor to a rank-equivalent tensor of unknown size, i.e. <1x2xf32> ->
 // <?x?xf32>
-Value dynamicCast(OpBuilder &b, Location loc, Value tensor);
-
+Value removeSizeInformation(OpBuilder &b, Location loc, Value tensor);
 } // namespace torch_to_linalg
 } // namespace torch
 } // namespace mlir
diff --git a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
@@ -980,8 +980,8 @@ class DecomposeAtenConvTranspose2dOp
     Value cstTrue = rewriter.create<Torch::ConstantBoolOp>(op.getLoc(), true);
     rewriter.replaceOpWithNewOp<AtenConvolutionOp>(
         op, op->getResultTypes(), op.input(), op.weight(), op.bias(),
-        op.stride(), op.padding(), op.dilation(), cstTrue, op.output_padding(),
-        op.groups());
+        op.stride(), op.padding(), op.dilation(), /*transposed=*/cstTrue,
+        op.output_padding(), op.groups());
 
     return success();
   }