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Results 1 - 2 of 2 for 256x16x32x32xf32 (0.21 sec)

  2. github.com/tensorflow/tensorflow

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

    }

func.func @Conv2dNCHW(%arg0: tensor<256x3x32x32xf32>, %arg1: tensor<3x3x3x16xf32>) -> tensor<256x16x32x32xf32> {
  %0 = "tf.Conv2D"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NCHW", dilations = [1, 1, 1, 1], padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<256x3x32x32xf32>, tensor<3x3x3x16xf32>) -> tensor<256x16x32x32xf32>
  func.return %0 : tensor<256x16x32x32xf32>

  // LAYOUT-LABEL: Conv2dNCHW
  // LAYOUT: "tfl.conv_2d"
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/tests/prepare-tf-with-allowing-bf16-and-f16-type-legalization.mlir 

      // CHECK: "tf.FusedBatchNormV3"
}

// CHECK-LABEL: depthwise_conv_2d_bf16
func.func @depthwise_conv_2d_bf16(%arg0 : tensor<256x32x32x3xbf16>, %arg1 : tensor<3x3x3x4xf32>, %arg2 : tensor<256x3x32x32xf32>) -> tensor<256x30x30x12xbf16> {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 26 23:53:32 UTC 2022
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