o ?e$@s.dZddlmZmZmZmZmZmZddlm Z ddl m Z ddl m Z ddl mZddl mZddlmZdd lmZdd lmZdd lmZ dd edefdedefdeeedeejdedef ddZ ddededeejeffdeeejdeejdedeejf ddZd S)z?szwhile_loop..cSg|]}|jqSrZdtyperrrrrAzVSupplied loop body function cannot be called with the specified inputs. You specified z inputs: cSrrrrirrrrJr z, but the loop body needs cSrrr!r"rrrrOr z and z: additional inputs from infeed, but the computation needs z[Supplied loop condition function cannot be called with the specified inputs. You specified cSrrr!r"rrrrWr z, but the loop condition needs cSrrr!r"rrrr\r z7. Note that infeed is not passed to the loop condition.csdkrg}|S)Nrr)r)r input_arityrrcondition_wrapper`sz%while_loop..condition_wrapperc s@t|}dkr g}r(tj}|durtd|ddD}ng}||}t|ttfs:|f}dd|D}dd|D}dd|D}|||krYtd d d|D}|krlt d |||7}|swt d}|rt j||d }tjrtj}|durd }t}|t|d|}|S)zBWrapper around `body` that handles infeed queues and control deps.rNzCan't build training loop with infeed when there is no tpu_shard_context. Are you building a loop or graph directly rather than from inside tpu.rewrite, tpu.batch_parallel, tpu.shard, or tpu.replicate?cSsg|]}|qSrr)rdrrrrwsz4while_loop..body_wrapper..cSs&g|]}t|tjr |nt|qSr) isinstancer OperationrrorrrrscSsg|] }t|tjr|qSrr'r r(r)rrrrscSsg|] }t|tjs|qSrr+r)rrrrs  zbTPU training loop body must return zero or more Tensor values followed by zero or more Operations.cSrrr)roprrrrr zNMismatch between input types and output types for training loop body: {} vs {})Zcontrol_inputs)listrZget_tpu_contextnumber_of_shards ValueErrorZset_number_of_shardsZgenerate_dequeue_opr'tuple TypeErrorformatr constantr r Z TensorTracer is_enabledZ trace_tpur Zget_default_graph) rr/Z dequeue_opsoutputsZoutput_operationsZoutput_tensorsZ output_typesZ num_replicastt)rrr$ input_typesrr body_wrapperfsZ        z while_loop..body_wrapperrr-)rZparallel_iterations) lenrZcheck_function_argument_countr2Znumber_of_tuple_elementsr r4 while_loop_tfr ) rrrrrZbody_arg_errorZcondition_arg_errorr%r9r)rrrr$r8rr sz    J  r ncszddfdd}fdd}|durdgndg|}t|||||d }|}t|d kr7|djS|d dS) aBuilds a training loop that executes a fixed number of iterations. The set of loop-carried tensors correspond to `inputs`. `body` must be a function that takes and returns the values of the loop-carried tensors. Args: n: the number of loop iterations body: a Python function that builds the loop body. inputs: a list of initial values passed into the training loop or None (equivalent to an empty list). infeed_queue: if not None, the infeed queue from which to append a tuple of arguments as inputs to condition. name: (Deprecated) Does nothing. Returns: The final values of the loop-carried tensors. Raises: ValueError: if there is a type error. cSst|ttfs |gSt|SN)r'r.r1)Zxsrrr_convert_to_listsz repeat.._convert_to_listcs ~|kSr>rr#args)r=rrcondszrepeat..condcs|dg|S)Nr-rr@)r?rrrr9szrepeat..body_wrapperNr)rrrr-)r r;r,)r=rrrrrBr9r6r)r?rr=rrepeats     rC)NNN)__doc__typingrrrrrrZtensorflow.python.compiler.xlarZtensorflow.python.frameworkr Ztensorflow.python.opsr r r r<Ztensorflow.python.tpur rrZtensorflow.python.typesrZ core_typesZ InfeedQueueintZ TensorLikerCrrrrsT