y_reshape - Code Search

tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py

      ]
      y_signature = [
          None if c not in contracting_dims else y_shape[cidx]
          for cidx, c in enumerate(y_labels)
      ]
    return x_shape, y_shape, bias_shape, x_signature, y_signature

  def _create_einsum_model(
      self,
      equation: str,
      y_shape: Sequence[int],
      x_signature: Sequence[Optional[int]],
      y_signature: Sequence[Optional[int]],

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_without_identity.pbtxt

# MLIR:         %[[reshape:.*]] = "tfl.reshape"(%[[conv]], %[[shape]]) : (tensor<1x1x1x186x!quant.uniform<i8:f32, 0.09363494573854933:22>>, tensor<3xi32>)
# MLIR:         return %[[reshape]] : tensor<1x6x31x!quant.uniform<i8:f32, 0.09363494573854933:22>>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_without_identity_4bit.pbtxt

# MLIR:         %[[reshape:.*]] = "tfl.reshape"(%[[conv]], %[[shape]]) : (tensor<1x1x1x186x!quant.uniform<i8:f32, 0.09363494573854933:22>>, tensor<3xi32>)
# MLIR:         return %[[reshape]] : tensor<1x6x31x!quant.uniform<i8:f32, 0.09363494573854933:22>>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir

  %1 = "tf.Reshape"(%0, %cst_0) : (tensor<1x2xf32>, tensor<2xi64>) -> tensor<2x1xf32>
  %2 = "tf.Reshape"(%0, %cst_0) : (tensor<1x2xf32>, tensor<2xi64>) -> tensor<2x1xf32>
  func.return %1, %2 : tensor<2x1xf32>, tensor<2x1xf32>

// CHECK:  %cst = arith.constant
// CHECK:  %[[FQ:.*]] = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
// CHECK:  %[[R1:.*]] = "tf.Reshape"(%[[FQ]], %cst)
// CHECK-SAME: tensor<2x1xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel.pbtxt

# MLIR:         %[[reshape:.*]] = "tfl.reshape"(%[[conv]], %[[shape]]) : (tensor<1x1x1x186x!quant.uniform<i8:f32, 0.09363494573854933:22>>, tensor<3xi32>)
# MLIR:         return %[[reshape]] : tensor<1x6x31x!quant.uniform<i8:f32, 0.09363494573854933:22>>
# MLIR:       }

# CHECK-LABEL: {
# CHECK:   version: 3,

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github.com/tensorflow/tensorflow

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

  // CHECK: %[[reshape:.*]] = stablehlo.reshape %[[dq]]
  %1 = stablehlo.reshape %0 : (tensor<2x3xf32>) -> (tensor<6xf32>)
  // CHECK: %[[q:.*]] = "quantfork.qcast"(%[[reshape]])
  // CHECK-SAME: -> tensor<6x!quant.uniform<i8:f32, 0.0078408040252386357:-1>>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir

  // Verify filter transformation for grouped convolution.

  // CHECK: %[[RESHAPE:.*]] = mhlo.reshape %arg0 : (tensor<2x2x5x21xf32>) -> tensor<2x2x5x3x7xf32>
  // CHECK: %[[TRANSPOSE:.*]] = "mhlo.transpose"(%[[RESHAPE]])
  // CHECK-SAME: permutation = dense<[0, 1, 3, 2, 4]>
  // CHECK-SAME: (tensor<2x2x5x3x7xf32>) -> tensor<2x2x3x5x7xf32>
  // CHECK: mhlo.reshape %[[TRANSPOSE]] : (tensor<2x2x3x5x7xf32>) -> tensor<2x2x15x7xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py

  )
  def test_einsum_ptq_model(
      self,
      equation: str,
  ):
    _, y_shape, bias_shape, x_signature, y_signature = (
        self._prepare_sample_einsum_datashapes(equation, use_bias=True)
    )

    model = self._create_einsum_model(
        self._input_saved_model_path,
        equation,
        y_shape,
        x_signature,
        y_signature,
        bias_shape,
    )

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir

  %1 = "tf.Reshape"(%0, %cst_0) : (tensor<1x2xf32>, tensor<2xi64>) -> tensor<2x1xf32>
  %2 = "tf.Reshape"(%0, %cst_0) : (tensor<1x2xf32>, tensor<2xi64>) -> tensor<2x1xf32>
  func.return %1, %2 : tensor<2x1xf32>, tensor<2x1xf32>

// CHECK:  %cst = arith.constant
// CHECK:  %[[FQ:.*]] = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
// CHECK:  %[[R1:.*]] = "tf.Reshape"(%[[FQ]], %cst)
// CHECK-SAME: tensor<2x1xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir

  %3 = "tfl.reshape"(%1, %2) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x128x128xf32>, tensor<2xi32>) -> tensor<128x128xf32>
  %4 = "tfl.relu"(%3) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<128x128xf32>) -> tensor<128x128xf32>
  %5 = "tfl.pseudo_const"() {value = dense<[1, 128, 128]> : tensor<3xi32>} : () -> tensor<3xi32>

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