2x3x3x2xi8 - Code Search

tensorflow/compiler/mlir/quantization/stablehlo/tests/bridge/optimize.mlir

  return %2 : tensor<?x2x2x1xi32>
}

// -----

// CHECK-LABEL: func @convolution_add_add_static
func.func @convolution_add_add_static(
    %lhs: tensor<2x3x2x1xi8>, %rhs: tensor<2x1x1x1xi8>,
    %zp_offset: tensor<2x2x2x1xi32>, %bias: tensor<1xi32>
  ) -> tensor<2x2x2x1xi32> {
  // CHECK-DAG: %[[conv:.*]] = mhlo.convolution

Registered: Sun Jun 16 05:45:23 UTC 2024

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_xla.mlir

// CHECK-SAME: (tensor<1x2x2x3xi8>, tensor<2x2x3x2xi8>, tensor<2xi32>, tensor<f32>, tensor<i32>, tensor<2xf32>, tensor<2xi32>, tensor<2xf32>, tensor<2xi32>, tensor<f32>, tensor<i32>) -> tensor<*xf32>
// CHECK: return %[[conv_quant]]

// CHECK-LABEL: func private @quantized_conv2d_with_bias_and_relu6_float_output_fn_0

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq_per_channel.mlir

// CHECK: %[[dq0:.*]] = "quantfork.dcast"(%[[q0]])

// CHECK: %[[q1:.*]] = "quantfork.qcast"(%[[cst_1]]) {volatile}
// CHECK-SAME: tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32:3, {0.075176584439014829,0.072960192762960605}>>
// CHECK: %[[dq1:.*]] = "quantfork.dcast"(%[[q1]])

// CHECK: %[[q2:.*]] = "quantfork.qcast"(%arg0)

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_xla.mlir

// CHECK: %[[minimum2:.*]] = "tf.Minimum"(%[[maximum2]]
// CHECK: %[[round2:.*]] = "tf.Round"(%[[minimum2]]
// CHECK: %[[quant2:.*]] = "tf.Cast"(%[[round2]]) <{Truncate = false}> : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xi8>

// CHECK: %[[pad2:.*]] = "tf.PadV2"(%[[quant2]]
// CHECK: %[[xlaconv2:.*]] = "tf.XlaConvV2"(%[[pad2]]
// CHECK: %[[sub2:.*]] = "tf.Sub"(%[[xlaconv2]]

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/decompose-hybrid-quantization.mlir

func.func @test_depthwise_conv2d_replace_float(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x112x112x32xf32> {
  // CHECK-DAG: %[[VAL0:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<{{.+}}>>, value = dense<42> : tensor<32x3x3x3xi8>}>
  // CHECK-DAG: %[[VAL1:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x!quant.uniform<{{.+}}>>, value = dense<0> : tensor<32xi32>}>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_lifting.mlir

  %0 = "quantfork.qcast"(%cst_1) : (tensor<2x3x3x2xf32>) -> tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32:3, {0.003937007874015748,0.003937007874015748}>>
  %1 = "quantfork.dcast"(%0) : (tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32:3, {0.003937007874015748,0.003937007874015748}>>) -> tensor<2x3x3x2xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/post-quantize.mlir

  %1 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq.mlir

// CHECK-SAME: tensor<2x!quant.uniform<i32:f32, 0.044169864606680966>>
// CHECK: %[[dq0:.*]] = "quantfork.dcast"(%[[q0]])

// CHECK: %[[q1:.*]] = "quantfork.qcast"(%[[cst_1]]) {volatile}
// CHECK-SAME: tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32, 0.075176584439014829>>
// CHECK: %[[dq1:.*]] = "quantfork.dcast"(%[[q1]])

// CHECK: %[[q2:.*]] = "quantfork.qcast"(%arg0)

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/quantize.mlir

// CHECK: %[[cst1:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 1.000000e-01>>, value = dense<1> : tensor<32x3x3x3xi8>}>
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[cst1]], %[[cst0]])
// CHECK: return %[[conv]] : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}

// CHECK-LABEL: QuantizeConv2D4Bit

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/quantize-numeric-verify.mlir

  %3 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>
  %4 = "tfl.dequantize"(%3) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>) -> tensor<32x3x3x3xf32>

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