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Results 1 - 5 of 5 for 11x7xf32 (0.12 sec)

  2. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/tpu_cluster_formation.mlir 

    // CHECK-SAME: (%[[ARG_0:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_1:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_2:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>, %[[ARG_3:[a-z0-9]*]]: tensor<!tf_type.resource<tensor<10x3xf32>>>)
!rtype = tensor<!tf_type.resource<tensor<10x3xf32>>>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 22:03:30 UTC 2024
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  3. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions.mlir 

        return %2 : tensor<1x2xf32>
  }

  func.func private @composite_add_fn(%arg0: tensor<1x2xf32>, %arg1: tensor<1x2xf32>) -> tensor<1x2xf32> attributes {_from_xla_call_module} {
    %0 = stablehlo.add %arg0, %arg1 : tensor<1x2xf32>
    %1 = stablehlo.add %0, %arg1 : tensor<1x2xf32>
    return %1 : tensor<1x2xf32>
  }
}

// -----
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 09 05:56:10 UTC 2024
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  4. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/tensor_array_ops_decomposition.mlir 

      // CHECK: %[[OLD_SLICE1:.*]] = "tf.Slice"(%[[READ1]],
  // CHECK: %[[RESHAPE1:.*]] = "tf.Reshape"(%[[VALUE]],
  // CHECK: %[[ADD1:.*]] = "tf.AddV2"(%[[RESHAPE1]], %[[OLD_SLICE1]]) : (tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<1x3xf32>
  // CHECK: %[[UPDATE1:.*]] = "tf.XlaDynamicUpdateSlice"(%[[READ1]], %[[ADD1]],
  // CHECK: "tf.AssignVariableOp"(%[[GVAR1]], %[[UPDATE1]])
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
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  5. github.com/tensorflow/tensorflow

    tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir 

      // CHECK-DAG: %[[ITEMS0_0:.*]] = "tf.ExpandDims"(%[[ITEMS0]], %[[AXIS]])
  // CHECK-DAG: "tf.ConcatV2"(%[[ITEMS1_3]], %[[ITEMS1_2]], %[[ITEMS1_1]], %[[ITEMS1_0]], %[[ITEMS0_0]], %[[AXIS]]) : (tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<1x2xf32>, tensor<i64>) -> tensor<5x2xf32>

  %indices0 = "tf.Const"() {value = dense<4> : tensor<i32>} : () -> tensor<i32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Fri Jan 05 18:35:42 UTC 2024
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  6. 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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