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Results 1 - 6 of 6 for QuantizeOp (0.19 sec)
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tensorflow/compiler/mlir/lite/transforms/quantize.cc
}; class QuantizeConstPattern : public OpRewritePattern<QuantizeOp> { public: explicit QuantizeConstPattern(MLIRContext* context, bool legacy_float_scale) : OpRewritePattern<QuantizeOp>(context), legacy_float_scale_(legacy_float_scale) {} LogicalResult matchAndRewrite(QuantizeOp op, PatternRewriter& rewriter) const override {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/post_quantize.cc
arg.dropAllUses(); bb.eraseArgument(0); }; // This is looking for a pattern: arg -> tfl.quantize if (arg.hasOneUse() && llvm::isa<QuantizeOp>(*arg.user_begin())) { auto quantize_op = llvm::cast<QuantizeOp>(*arg.user_begin()); remove_quantize_op(quantize_op); continue; } // Make a copy of current argument and append it to the end of the list if
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.h
// A base rewrite pattern which matches any N-in-M-out operations with // quantization parameters propagated to at least one of its operands. The // quantization parameters are annotated by the QuantizeOp/DequantizeOp pairs. // Each matched pattern are rewritten by its quantized alternatives. // // Quantization method is determined by the `_quantization_method` attributes // attached to each quantizable units. //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h
if (QuantizedType::getQuantizedElementType(quantize_operand.getType())) { // The input of this QuantizeOp has already been quantized, i.e. // rescale. return failure(); } DenseFPElementsAttr attr; if (matchPattern(quantize_operand, m_Constant(&attr))) { // Const-> QuantizeOp pattern will be handled separately. return failure(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.cc
rewriter.create<TFL::MeanOp>(mean_op->getLoc(), new_output_type, input, mean_op.getAxis(), mean_op.getKeepDims()); // Insert a requant op. rewriter.replaceOpWithNewOp<TFL::QuantizeOp>( mean_op, output_type, new_mean_op, mlir::TypeAttr::get(output_type)); return success(); } } // namespace tac } // namespace TFL
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/quantization/stablehlo/passes/quantization_patterns.cc
output_types.push_back(result_type); continue; } const Type result_element_type = mlir::cast<TensorType>(result.getType()).getElementType(); // If the user is the QuantizeOp, it must be the only user. if (result.hasOneUse() && isa<quantfork::QuantizeCastOp>(*result.user_begin())) { auto user = cast<quantfork::QuantizeCastOp>(*result.user_begin());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 06:04:36 UTC 2024 - 41.7K bytes - Viewed (0)