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Results 1 - 3 of 3 for 16x16xf32 (0.1 sec)

  2. github.com/tensorflow/tensorflow

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

    func.func @QuantizedCatsAddRequantsTest(%arg0: tensor<1x1xf32>, %arg1: tensor<1x1xf32>, %arg2: tensor<1x1xf32>, %arg3: tensor<1x1xf32>) -> (tensor<1x4xf32>, tensor<1x3xf32>) {
  %0 = "quantfork.stats"(%arg0) {layerStats = dense<[-0.440728068, 0.189515018]> : tensor<2xf32>} : (tensor<1x1xf32>) -> tensor<1x1xf32>
  %1 = "quantfork.stats"(%arg1) {layerStats = dense<[-0.154693216, 0.26483655]> : tensor<2xf32>} : (tensor<1x1xf32>) -> tensor<1x1xf32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md 

    For example, if we have the code

```mlir
  %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32>
  %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32>
  %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32>
```

then running this pass with 'default-device=foobar', we get:

```mlir
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Aug 02 02:26:39 UTC 2023
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  4. github.com/tensorflow/tensorflow

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

      func.return %0 : tensor<10x10xf32>
  // CHECK-LABEL: strided_slice_with_constant_attributes
  // CHECK-DAG: [[BEGIN:%cst.*]] = arith.constant dense<[-1, 0, 0]> : tensor<3xi32>
  // CHECK-DAG: [[END:%cst.*]] = arith.constant dense<[0, 10, 10]> : tensor<3xi32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 29 07:26:59 UTC 2024
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