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Results 1 - 2 of 2 for 2x3x5x4xf32 (0.2 sec)

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

    func.func @ConvertSliceToIdentityI32(%arg0: tensor<2x3x4x5xf32>) -> tensor<2x3x4x5xf32> {
      %begin = arith.constant dense<0> : tensor<4xi32>
      %shape = arith.constant dense<[2,3,4,5]> : tensor<4xi32>
      %0 = "tfl.slice"(%arg0, %begin, %shape) : (tensor<2x3x4x5xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<2x3x4x5xf32>
      func.return %0 : tensor<2x3x4x5xf32>
      // CHECK: return %arg0
    }
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 16 20:31:41 UTC 2024
    - 284.1K bytes
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  2. tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir

    func.func @maxpool_explicit_padding(%arg0: tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32> {
      // CHECK: tf.MaxPool
      // TODO(b/165938852): need to support explicit padding in max_pool.
    
      %0 = "tf.MaxPool"(%arg0) {data_format = "NHWC", ksize = [1, 2, 2, 1], padding = "EXPLICIT", strides = [1, 4, 4, 1]} : (tensor<2x12x20x7xi32>) -> tensor<2x3x5x7xi32>
      func.return %0 : tensor<2x3x5x7xi32>
    }
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon May 06 18:46:23 UTC 2024
    - 335.5K bytes
    - Viewed (0)
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