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Results 1 - 2 of 2 for output_sharding_configuration (0.33 sec)

  1. tensorflow/compiler/mlir/tfrt/tests/ifrt/rewrite_cluster_to_ifrt_call.mlir

      %0 = "tf_device.cluster_func"(%arg0) {_producer_name = "UNKNOWN", func = @_func, input_sharding_configuration = [""], num_cores_per_replica = 1 : i64, device_assignment = [], topology = "", output_sharding_configuration = [""], step_marker_location = "STEP_MARK_AT_ENTRY", use_spmd_for_xla_partitioning = false, use_tpu = true} : (tensor<1x3xf32>) -> (tensor<1x3xf32>)
      return %0 : tensor<1x3xf32>
    }
    
    // CHECK-LABEL: @_func
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Sat Feb 17 07:28:40 UTC 2024
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  2. tensorflow/compiler/mlir/tensorflow/utils/xla_sharding_util.h

    namespace tensorflow {
    
    inline constexpr llvm::StringRef kInputShardingAttr =
        "input_sharding_configuration";
    inline constexpr llvm::StringRef kOutputShardingAttr =
        "output_sharding_configuration";
    
    // Parses the sharding string. This sharding string can be binary (serialized)
    // or human readable.
    mlir::LogicalResult DecodeShardingAttribute(const std::string& shard_str,
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Mar 28 22:18:34 UTC 2024
    - 6K bytes
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