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Results 1 - 4 of 4 for 1x114x114x64xf32 (0.1 sec)

  2. github.com/tensorflow/tensorflow

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

    // CHECK-SAME:          %[[INPUT:.*]]: tensor<1x112x112x64xf32>,
// CHECK-SAME:          %[[PAD_VAL:.*]]: tensor<f32>) -> tensor<1x64x114x114xf32> {
// CHECK:           %[[PAD:.*]] = stablehlo.pad %[[INPUT]], %[[PAD_VAL]],
// CHECK:               low = [0, 1, 1, 0], high = [0, 1, 1, 0], interior = [0, 0, 0, 0]
// CHECK:               : (tensor<1x112x112x64xf32>, tensor<f32>) -> tensor<1x114x114x64xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 21:59:06 UTC 2024
    - 2.8K bytes
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_end.mlir 

             exponential_avg_factor = 1.0 : f32,
         is_training = false
       }
        : (tensor<1x112x112x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>)
       -> (tensor<1x112x112x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>)

  func.return %2#0 : tensor<1x112x112x64xf32>
}

// CHECK-LABEL: func @fold_into_pad_with_extra_uses
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 9.5K bytes
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  4. github.com/tensorflow/tensorflow

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

      %dconv_s = "quantfork.stats"(%dconv) {layerStats = dense<[0.000000e+00, 1.000000e+01]> : tensor<2xf32>} : (tensor<1x112x112x64xf32>) -> tensor<1x112x112x64xf32>
  %bmm = "tfl.batch_matmul"(%conv_s, %dconv_s) {adj_x = false, adj_y = true} : (tensor<1x112x112x64xf32>, tensor<1x112x112x64xf32>) -> tensor<1x112x112x112xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 38.2K bytes
    - Viewed (0)
  5. github.com/tensorflow/tensorflow

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

      func.return %conv : tensor<1x112x112x64xf32>

// CHECK: %[[b:.*]] = arith.constant dense<-1.23697901> : tensor<64xf32>
// CHECK: %[[w:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<64x3x3x3x!quant.uniform<i8<-127:127>:f32:0, {
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[w]], %[[b]]) <{
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 23 21:09:00 UTC 2024
    - 23.2K bytes
    - Viewed (0)
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