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Results 1 - 4 of 4 for 1x5x5x1024xf32 (0.12 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/unfreeze_constants.mlir 

        %1 = "tf.AddV2"(%0#2, %cst_2) {device = ""} : (tensor<1x5x5x1024xf32>, tensor<1x5x5x1024xf32>) -> tensor<1x5x5x1024xf32>
    return %1 : tensor<1x5x5x1024xf32>
  }

  func.func private @while_body(%arg0: tensor<i32> {tf._user_specified_name = "while/loop_counter"}, %arg1: tensor<i32> {tf._user_specified_name = "while/maximum_iterations"}, %arg2: tensor<1x5x5x1024xf32>) -> (tensor<i32>, tensor<i32>, tensor<1x5x5x1024xf32>)
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 17.2K bytes
    - Viewed (0)
  3. github.com/tensorflow/tensorflow

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

        %2 = "quantfork.qcast"(%1) : (tensor<1x3x2x1024xf32>) -> tensor<1x3x2x1024x!quant.uniform<i8:f32, 0.0011764706057660721:-43>>
    %3 = "quantfork.dcast"(%2) : (tensor<1x3x2x1024x!quant.uniform<i8:f32, 0.0011764706057660721:-43>>) -> tensor<1x3x2x1024xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Jan 08 01:16:10 UTC 2024
    - 25.2K bytes
    - Viewed (0)
  4. github.com/tensorflow/tensorflow

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

    // CHECK:           [[VAL_7:%.*]] = "tfl.slice"([[VAL_1]], [[VAL_3]], [[VAL_5]]) : (tensor<1x8x8x1024xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x8x8x256xf32>
// CHECK:           [[VAL_8:%.*]] = "tfl.slice"([[VAL_1]], [[VAL_4]], [[VAL_5]]) : (tensor<1x8x8x1024xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x8x8x256xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 15.6K bytes
    - Viewed (0)
  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_weights.mlir 

        %2 = "tf.Conv2D"(%1, %cst_1) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x3x2x1024xf32>, tensor<3x3x1024x1xf32>) -> tensor<1x3x1x1xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 42K bytes
    - Viewed (0)
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