tf_quant__ - Code Search

tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir

// -----

// No CustomAggregator ops exist.
func.func private @composite_conv2d_with_bias_and_relu6_fn_1(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>, %arg2: tensor<2xf32>) -> tensor<1x2x2x2xf32> attributes {tf_quant.composite_function} {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir

// DISABLE-ALL-DOT-GENERAL: return %[[XLA_CALL_MODULE:.+]] : tensor<1x1x64xf32>
// DISABLE-ALL-DOT-GENERAL: }

// DISABLE-ALL-DOT-GENERAL-LABEL: private @composite_dot_general_fn_1
// DISABLE-ALL-DOT-GENERAL-SAME: tf_quant.composite_function
// DISABLE-ALL-DOT-GENERAL: %[[DOT_GENERAL:.+]] = stablehlo.dot_general %arg0, %arg1
// DISABLE-ALL-DOT-GENERAL: return %[[DOT_GENERAL:.+]] : tensor<1x1x64xf32>
// DISABLE-ALL-DOT-GENERAL: }

// -----

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/replace_stablehlo_ops_in_main_function_with_xla_call_module_ops.mlir

  // CHECK: }

  // CHECK: @composite_dot_general_fn_1
  // CHECK-NOT: tf_quant.composite_function
  func.func private @composite_dot_general_fn_1(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>, %arg2: tensor<1x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/passes/insert_quantized_functions.cc

    // For consistency, we require all quantized composite function to have
    // the "tf_quant.quantized_ops" attribute.
    if (!new_func.getSymName().starts_with("quantized_")) continue;
    if (!new_func->hasAttrOfType<ArrayAttr>("tf_quant.quantized_ops")) {
      new_func->emitError() << "Missing \"tf_quant.quantized_ops\" "
                               "attribute in the quantized composite function.";

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir

    func.return %add : tensor<*xf32>
  }

  func.func @composite_conv2d_with_relu6_fn(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc

constexpr absl::string_view kModuleLifted = R"mlir(
  module {
    func.func private @composite_dot_general_fn_1(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
      %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x1024xf32>, tensor<1024x3xf32>) -> tensor<1x3xf32>
      return %0 : tensor<1x3xf32>
    }

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_drq.mlir

    func.return %1: tensor<*xf32>
  }
  func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
    %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op.mlir

    func.return %0, %1 : tensor<*xf32>, tensor<*xf32>
  }
  func.func private @composite_conv2d_with_bias_and_relu6_fn_2(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x2x3x2xf32>, %arg2: tensor<2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc

      return %2 : tensor<?x2xf32>
    }
    func.func private @composite_fn_1(%arg0: tensor<?x2xf32>, %arg1: tensor<2x2xf32>, %arg2: tensor<2xf32>) -> tensor<?x2xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
      return %arg0 : tensor<?x2xf32>
    }
  }
)mlir";

constexpr absl::string_view kModuleDotWeightOnlyPtq = R"mlir(
  module {

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op_stablehlo.mlir

    return %3 : tensor<?x2xf32>
  }
  func.func private @composite_dot_general_with_bias_and_relu6_dynamic_fn_2(%arg0: tensor<?x2xf32>, %arg1: tensor<2x2xf32>, %arg2: tensor<2xf32>) -> tensor<?x2xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
    %0 = stablehlo.constant dense<0.000000e+00> : tensor<f32>
    %1 = stablehlo.constant dense<6.000000e+00> : tensor<f32>

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- Last Modified: Fri Mar 22 22:55:22 UTC 2024

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