o ?e+ @sdZddlZddlmZddlmZddlmZddlm Z ddl m Z ddlmZdd l mZdd l mZdd l mZdd lmZdd lmZddlmZddlmZm Z edej!ej"ej#ej$ej%Z&d'dej'e&de(de)de(dej'e&f ddZ*ede+e*Z,dej'e&de(de)de(dej'e&f ddZ-edej!ej"ej#ej$ej%Z.d'dej'e.dej'e.fddZ/ede+e/Z0dej'e.dej'e.fdd Z1ed!ej!ej"ej#ej$ej%Z2d'de ej'e2de(dej'e2fd"d#Z3ed$e+e3Z4de ej'e2de(dej'e2fd%d&Z5dS)(zUPython wrappers around TensorFlow ops. This file is MACHINE GENERATED! Do not edit. N) pywrap_tfe)context)core)execute)dtypes)annotation_types)op_def_registry)ops)op_def_library)deprecated_endpoints)dispatch) tf_export)TypeVarListTV_NcclAllReduce_Tinput reduction num_devices shared_namereturnc CsPtjpt}|j}|jrWzt|d||d|d|d| }|WStjy7}z t ||WYd}~nd}~wtj y@Ynwz t ||||||dWStj yVYnwt |d}t |d}t |d}tjd|||||d\} } } } | dd}t rd| dd| dd| dd| df} | j} t d| | ||\}|S) aOutputs a tensor containing the reduction across all input tensors. Outputs a tensor containing the reduction across all input tensors passed to ops within the same `shared_name. The graph should be constructed so if one op runs with shared_name value `c`, then `num_devices` ops will run with shared_name value `c`. Failure to do so will cause the graph execution to fail to complete. input: the input to the reduction data: the value of the reduction across all `num_devices` devices. reduction: the reduction operation to perform. num_devices: The number of devices participating in this reduction. shared_name: Identifier that shared between ops of the same reduction. Args: input: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. reduction: A `string` from: `"min", "max", "prod", "sum"`. num_devices: An `int`. shared_name: A `string`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `input`. NcclAllReducerrrN)rrrnamectx)rrrrrT)_contextr_thread_local_datais_eagerrTFE_Py_FastPathExecute_core_NotOkStatusException_opsraise_from_not_ok_status_FallbackExceptionnccl_all_reduce_eager_fallback_SymbolicException_executemake_strmake_int_op_def_library_apply_op_helpermust_record_gradientget_attr_get_attr_type _get_attr_intinputsrecord_gradient)rrrrr_ctxtld_resulte__op_outputs_attrs _inputs_flatr9c/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/ops/gen_nccl_ops.pynccl_all_reducesX        r;zraw_ops.NcclAllReducec Cst|d}t|d}t|d}t|g|tjtjtjtjtj g\}\}|g}d|d|d|d|f}tj dd||||d} t rKt d||| | \} | S) Nrrrrs NcclAllReducer.attrsrrr) r%r&r'args_to_matching_eager_dtypeshalffloat32float64int32int64rr*r/) rrrrrr_attr_Tr8r7r2r9r9r:r#]s"   *  r#TV_NcclBroadcast_Tc Cstjpt}|j}|jrQz t|d||d|}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t ||||dWStj yPYnwt |d}tjd|||d\}}}} | dd}t rd|dd|df} |j} t d| | ||\}|S)aSends `input` to all devices that are connected to the output. Sends `input` to all devices that are connected to the output. The graph should be constructed so that all ops connected to the output have a valid device assignment, and the op itself is assigned one of these devices. input: The input to the broadcast. output: The same as input. shape: The shape of the input tensor. Args: input: A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. shape: A `tf.TensorShape` or list of `ints`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `input`. NcclBroadcastshapeN)rIrr)rrIrr)rrrrrrrrr r!r"nccl_broadcast_eager_fallbackr$r% make_shaper(r)r*r,r+r.r/) rrIrr0r1r2r3r4r5r6r7r8r9r9r:nccl_broadcastpsD   rLzraw_ops.NcclBroadcastc Cst|d}t|g|tjtjtjtjtjg\}\}|g}d|d|f}tj dd||||d}t r;t d||||\}|S)NrIrs NcclBroadcastr<r=rH) r%rKr?r@rArBrCrDrErr*r/)rrIrrrFr8r7r2r9r9r:rJs *  rJTV_NcclReduce_Tc Cs@tjpt}|j}|jrQz t|d||d|}|WStjy3}z t ||WYd}~nd}~wtj y<Ynwz t ||||dWStj yPYnwt |ttfs^td|t|}t|d}tjd|||d\}}} } | dd}trd| dd| dd| df} | j} td| | ||\}|S) aReduces `input` from `num_devices` using `reduction` to a single device. Reduces `input` from `num_devices` using `reduction` to a single device. The graph should be constructed so that all inputs have a valid device assignment, and the op itself is assigned one of these devices. input: The input to the reduction. data: the value of the reduction across all `num_devices` devices. reduction: the reduction operation to perform. Args: input: A list of at least 1 `Tensor` objects with the same type in: `half`, `float32`, `float64`, `int32`, `int64`. reduction: A `string` from: `"min", "max", "prod", "sum"`. name: A name for the operation (optional). Returns: A `Tensor`. Has the same type as `input`. 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