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Results 1 - 3 of 3 for 256x32x32x3xf32 (0.14 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/experimental/tac/tests/fold-constants-to-subgraph.mlir 

    }

// -----

module {
func.func @main(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {
  %0 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16x3x3x3xf32>} : () -> tensor<16x3x3x3xf32>
  %1 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16xf32>} : () -> tensor<16xf32>
  %2 = func.call @fold_all_test(%arg0, %0, %1) : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x30x30x16xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 10.5K bytes
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir 

    // CHECK:  %[[R2:.*]] = "tf.Reshape"(%[[FQ]], %cst)
// CHECK-SAME: tensor<2x1xf32>
}

// CHECK-LABEL: fakeQuantWithConv2D
func.func @fakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
^bb0(%arg: tensor<256x32x32x3xf32>) :
  %in = arith.constant dense<0.0> : tensor<3x3x3x16xf32>
  %min = arith.constant dense<0.0> : tensor<f32>
  %max = arith.constant dense<15.0> : tensor<f32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 22K bytes
    - Viewed (0)
  4. github.com/tensorflow/tensorflow

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

    // CHECK:  %[[R2:.*]] = "tf.Reshape"(%[[FQ]], %cst)
// CHECK-SAME: tensor<2x1xf32>
}

// CHECK-LABEL: fakeQuantWithConv2D
func.func @fakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
^bb0(%arg: tensor<256x32x32x3xf32>) :
  %in = arith.constant dense<0.0> : tensor<3x3x3x16xf32>
  %min = arith.constant dense<0.0> : tensor<f32>
  %max = arith.constant dense<255.0> : tensor<f32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 20.4K bytes
    - Viewed (0)
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