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Integrate LLVM at llvm/llvm-project@dc8d7d23d8

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Updates LLVM usage to match
[dc8d7d23d8d2](https://github.com/llvm/llvm-project/commit/dc8d7d23d8d2)

PiperOrigin-RevId: 329992306
Change-Id: I703863cedaf8c4e96b4209c965df58890718b69c
This commit is contained in:
A. Unique TensorFlower 2020-09-03 14:20:43 -07:00 committed by TensorFlower Gardener
parent 3137d96fa6
commit a05d0cda79
6 changed files with 7 additions and 7 deletions
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2
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
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@ -784,7 +784,7 @@ static StatusOr<FuncOp> PostProcessFuncOp(FuncOp func) {
auto new_output_type = new_qtype.castFromExpressedType(
mlir::quant::UniformQuantizedType::castToExpressedType(
value.getType()));
builder.setInsertionPointAfter(cst);
builder.setInsertionPointAfter(cst.getOperation());
auto new_op = builder.create<tfl::QConstOp>(
cst.getLoc(), new_output_type, mlir::TypeAttr::get(new_output_type),
cst.valueAttr());

2
tensorflow/compiler/mlir/lite/quantization/quantization_utils.h
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@ -119,7 +119,7 @@ struct ConvertStatsToQDQs : public OpRewritePattern<quant::StatisticsOp> {
return failure();
}
rewriter.setInsertionPointAfter(op);
rewriter.setInsertionPointAfter(op.getOperation());
Type result_type = quant_type.castFromExpressedType(op.getType());
auto q = rewriter.create<Q>(op.getLoc(), result_type, op.arg());
auto dq = rewriter.create<DQ>(op.getLoc(), op.getType(), q);

2
tensorflow/compiler/mlir/lite/quantization/tensorflow/tf_to_quant.cc
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@ -106,7 +106,7 @@ struct InsertQuantOpsAfterTFFakeQuantOp
}
// Use the min/max from the operands and the num_bits and narrow_range
// attribute to create the quantization parameter for the new quantize op.
rewriter.setInsertionPointAfter(tf_op);
rewriter.setInsertionPointAfter(tf_op.getOperation());
IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.num_bits());
BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.narrow_range());
Type res_type = tf_op.getType();

2
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
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@ -215,7 +215,7 @@ struct InsertTFLQuantOpsAfterTFFakeQuantOp
}
// Use the min/max from the operands and the num_bits and narrow_range
// attribute to create the quantization parameter for the new quantize op.
rewriter.setInsertionPointAfter(tf_op);
rewriter.setInsertionPointAfter(tf_op.getOperation());
IntegerAttr num_bits = rewriter.getI64IntegerAttr(tf_op.num_bits());
BoolAttr narrow_range = rewriter.getBoolAttr(tf_op.narrow_range());
Type res_type = tf_op.getType();

2
tensorflow/compiler/mlir/tensorflow/transforms/legalize_hlo.cc
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@ -250,7 +250,7 @@ class ConvertSliceOp : public OpConversionPattern<mhlo::SliceOp> {
strides.getSplatValue().cast<IntegerAttr>().getInt() != 1)
return failure();
rewriter.setInsertionPointAfter(slice_op);
rewriter.setInsertionPointAfter(slice_op.getOperation());
auto start_indices = slice_op.start_indices();
auto limit_indices = slice_op.limit_indices();
std::vector<int64_t> size_values;

4
tensorflow/workspace.bzl
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@ -722,8 +722,8 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
)
# Check out LLVM and MLIR from llvm-project.
LLVM_COMMIT = "1426ac0482951d4cb98f84ab9fc89c745f95602e"
LLVM_SHA256 = "51d7b55551523336dfbb122f5296a931d6053937c69a71d61749b1e6af53b153"
LLVM_COMMIT = "dc8d7d23d8d25e1ba4859c831151158ae6a617ef"
LLVM_SHA256 = "fe005ab69c846cd4eacb8c7ab479c7558ccf0edbd8e404c12d47427d30c7fc69"
LLVM_URLS = [
"https://storage.googleapis.com/mirror.tensorflow.org/github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),
"https://github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),