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Results 1 - 6 of 6 for 6x3x7x7xf32 (0.14 sec)

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

      %cst = "tf.Const"() <{value = dense<6.0> : tensor<6x3x7x7xf32>}> : () -> tensor<6x3x7x7xf32>
      %cst_14 = "tf.Const"() <{value = dense<[2, 3, 1, 0]> : tensor<4xi64>}> : () -> tensor<4xi64>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
    - 59.8K bytes
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  2. tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-with-tf2xla-hlo-importer.mlir

        func.return %result : tensor<10x24x24x64xf32>
      }
    
      // CHECK-LABEL: @max_pool_grad_same
      func.func @max_pool_grad_same(%orig_input: tensor<2x13x25x7xf32>, %orig_output: tensor<2x4x7x7xf32>, %grad: tensor<2x4x7x7xf32>) -> tensor<2x13x25x7xf32> {
        // CHECK: padding = dense<{{\[\[}}0, 0], [0, 1], [1, 1], [0, 0]]> : tensor<4x2xi64>
        %result = "tf.MaxPoolGrad"(%orig_input, %orig_output, %grad) {
          data_format = "NHWC",
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Sat Apr 06 15:32:52 UTC 2024
    - 38.6K bytes
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  3. tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir

      // CHECK-SAME: explicit_paddings = [1, 2, 7, 8, 3, 4, 5, 6]
      // CHECK-SAME: padding = "EXPLICIT"
      // CHECK-SAME: strides = [5, 8, 6, 7]
      // CHECK-SAME: (tensor<1x3x32x32xf32>, tensor<1x1x3x8xf32>) -> tensor<1x8x7x7xf32>
    
      // CHECK: %[[RES_PERM:.*]] = "tf.Const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi64>}>
      // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%[[CONV2D]], %[[RES_PERM]])
      // CHECK: return %[[RES_TRANSPOSE]]
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 9K bytes
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  4. tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir

    func.func @testBiasAdd(%arg0: tensor<2x3x5x7xf32>, %arg1: tensor<5x7xf32>) -> tensor<2x3x5x7xf32> {
      // expected-error @+1 {{requires bias operand to have rank exactly one}}
      %0 = "tf.BiasAdd"(%arg0, %arg1) {data_format = "NHWC"} : (tensor<2x3x5x7xf32>, tensor<5x7xf32>) -> tensor<2x3x5x7xf32>
      func.return %0 : tensor<2x3x5x7xf32>
    }
    
    // -----
    
    func.func @testBiasAdd(%arg0: tensor<2x3x5x7xf32>, %arg1: tensor<5xf32>) -> tensor<2x3x5x7xf32> {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 23 14:40:35 UTC 2023
    - 236.4K bytes
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  5. tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir

    // CHECK-SAME:                                %[[VAL_0:.*]]: tensor<4x3x16x16xf32>) -> tensor<4x3x7x7xf32> {
    // CHECK:           %[[VAL_1:.*]] = "tf.AvgPool"(%[[VAL_0]]) <{data_format = "NCHW", ksize = [1, 1, 3, 3], padding = "VALID", strides = [1, 1, 2, 2]}> : (tensor<4x3x16x16xf32>) -> tensor<4x3x7x7xf32>
    // CHECK:           return %[[VAL_1]] : tensor<4x3x7x7xf32>
    // CHECK:         }
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
    - 340.2K bytes
    - Viewed (0)
  6. tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir

      func.return %result : tensor<10x8x24x24x64xf32>
    }
    
    // -----
    
    // CHECK-LABEL: @max_pool_grad_same
    func.func @max_pool_grad_same(%orig_input: tensor<2x13x25x7xf32>, %orig_output: tensor<2x4x7x7xf32>, %grad: tensor<2x4x7x7xf32>) -> tensor<2x13x25x7xf32> {
      // CHECK: padding = dense<{{\[\[}}0, 0], [0, 1], [1, 1], [0, 0]]> : tensor<4x2xi64>
      %result = "tf.MaxPoolGrad"(%orig_input, %orig_output, %grad) {
         data_format = "NHWC",
    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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