1x1x1xf32 - Code Search

tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir

    %14 = stablehlo.multiply %12, %13 : tensor<1x4x3xf32>  // s1 * s2
    %15 = call @uniform_quantize_1(%14, %5, %6) : (tensor<1x4x3xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<1x4x3xi8>
    %16 = call @uniform_dequantize_0(%15, %5, %6) : (tensor<1x4x3xi8>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<1x4x3xf32>
    return %16 : tensor<1x4x3xf32>
  }

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- Last Modified: Tue May 14 17:10:32 UTC 2024

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir

                                      interior_padding = #vhlo.tensor_v1<dense<0> : tensor<3xi64>>}> : (tensor<1x160x1xf32>, tensor<f32>) -> tensor<1x161x1xf32>
  return %0 : tensor<1x161x1xf32>
}

//CHECK:func.func private @pad(%arg0: tensor<1x160x1xf32>, %arg1: tensor<f32>) -> tensor<1x161x1xf32> {
//CHECK-NEXT: %0 = "vhlo.pad_v1"(%arg0, %arg1) <{edge_padding_high = #vhlo.tensor_v1<dense<0> : tensor<3xi64>>,

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc

      return %0 : tensor<1x1x4xf32>
    }
  )mlir";

  OwningOpRef<ModuleOp> module_op =
      ParseModuleOpString(kModuleXlaCallModuleOpWithDefaultQuantizationMethod);
  ASSERT_TRUE(module_op);

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- Last Modified: Thu Apr 04 07:19:09 UTC 2024

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir

      time_major = false} : (
        tensor<1x2x3xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
        none, none, none,
        tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>,
        none, none,
        tensor<1x3xf32>, tensor<1x3xf32>,
        none, none, none, none) -> tensor<1x2x3xf32>

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- Last Modified: Thu May 02 09:41:17 UTC 2024

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github.com/tensorflow/tensorflow

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

      return %0 : tensor<1x1x4xf32>
    }
  )mlir";

  const OwningOpRef<ModuleOp> module_op =
      ParseModuleOpString(kXlaCallModuleOpWithQuantizationMethodAttr);
  ASSERT_TRUE(module_op);

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

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-gpu.mlir

// CHECK:           %[[VAL_6:.*]] = "tfl.reshape"(%[[VAL_1]], %[[VAL_2]]) : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32>
// CHECK:           %[[VAL_7:.*]] = "tfl.concatenation"(%[[VAL_5]], %[[VAL_6]]) <{axis = 3 : i32, fused_activation_function = "NONE"}> : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>

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- Last Modified: Thu May 02 09:41:17 UTC 2024

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/experimental/tac/README.md

    %1 = "tfl.reshape"(%arg1, %cst) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1xf32>, tensor<4xi32>) -> tensor<1x1x1x1xf32>
    %2 = "tfl.concatenation"(%0, %1) {axis = 3 : i32, fused_activation_function = "NONE", tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x2xf32>

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- Last Modified: Tue Mar 29 18:32:13 UTC 2022

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir

  // CHECK: %[[v1:.*]] = "tf.Reshape"(%arg1, %[[cst_1]]) : (tensor<5x2xf32>, tensor<3xi64>) -> tensor<5x2x1xf32>
  // CHECK: %[[v2:.*]] = "tf.BatchMatMulV2"(%[[v0]], %[[v1]]) <{adj_x = false, adj_y = false}> : (tensor<5x7x2xf32>, tensor<5x2x1xf32>) -> tensor<5x7x1xf32>
  // CHECK: %[[v3:.*]] = "tf.Reshape"(%[[v2]], %[[cst_2]]) : (tensor<5x7x1xf32>, tensor<2xi64>) -> tensor<5x7xf32>
  // CHECK: return %[[v3:.*]] : tensor<5x7xf32>
}

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github.com/tensorflow/tensorflow

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

  %custom_2 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32>
  %custom_3 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32>

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir

func.func @testRemoveReshapeAroundDot(%arg0: tensor<1x1x512xf32>, %arg1: tensor<512x13x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x1x13xf32> {
  %0 = "mhlo.reshape"(%arg0) : (tensor<1x1x512xf32>) -> tensor<1x512xf32>
  %1 = "mhlo.dot"(%0, %arg1) : (tensor<1x512xf32>, tensor<512x13x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x13xf32>
  %2 = "mhlo.reshape"(%1) : (tensor<1x13xf32>) -> tensor<1x1x13xf32>
  func.return %2 : tensor<1x1x13xf32>

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