σ VΎχXc@`sdZddlmZddlmZddlmZddlZddlmZddlm Z ddlm Z dd l m Z dd l mZdd lmZdd lmZdd lmZd„Zd„Zd„Zd„Zd„Zd„Zdddd„ZdS(sƒShim for systems that need to load both SessionBundle and SavedModel. This is intended to be used during migration to SavedModel. i(tabsolute_import(tdivision(tprint_functionN(t constants(t manifest_pb2(tsession_bundle(tmeta_graph_pb2(tsession(t meta_graph(tloader(tsignature_constantscC`s*tjd|ƒ}|j|j|ƒdS(sZAdd input tensor to signature_def. Args: tensor_name: string name of tensor to add to signature_def inputs map_key: string key to key into signature_def inputs map signature_def: object of type meta_graph_pb2.SignatureDef() Sideffect: adds a TensorInfo with tensor_name to signature_def inputs map keyed with map_key tnameN(Rt TensorInfotinputstCopyFrom(t tensor_nametmap_keyt signature_deft tensor_info((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt_add_input_to_signature_def#s cC`s*tjd|ƒ}|j|j|ƒdS(s^Add output tensor to signature_def. Args: tensor_name: string name of tensor to add to signature_def outputs map_key: string key to key into signature_def outputs map signature_def: object of type meta_graph_pb2.SignatureDef() Sideffect: adds a TensorInfo with tensor_name to signature_def outputs map keyed with map_key R N(RR toutputsR(RRRR((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt_add_output_to_signature_def3s cC`s |j}tjƒ}|jdƒdkrt|j}tj|_t|j j tj |ƒt |j j tj|ƒn‘|jdƒdkrμ|j}tj|_t|j j tj|ƒt |jj tj|ƒt |jj tj|ƒntd|jdƒƒ‚|S(s_Convert default signature to object of type SignatureDef. Args: signatures: object of type manifest_pb2.Signatures() Returns: object of type SignatureDef which contains a converted version of default signature from input signatures object Raises: RuntimeError: if default signature type is not classification or regression. ttypetregression_signaturetclassification_signaturesjOnly classification and regression default signatures are supported for up-conversion. %s is not supported(tdefault_signatureRt SignatureDeft WhichOneofRR tREGRESS_METHOD_NAMEt method_nameRtinputRtREGRESS_INPUTSRtoutputtREGRESS_OUTPUTSRtCLASSIFY_METHOD_NAMEtCLASSIFY_INPUTStclassestCLASSIFY_OUTPUT_CLASSEStscorestCLASSIFY_OUTPUT_SCORESt RuntimeError(t signaturesRRRR((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt+_convert_default_signature_to_signature_defDs4             cC`sύtjƒ}|jtj}|jtj}|jdƒdksV|jdƒdkrtd|jdƒ|jdƒfƒ‚ntj|_ x3|j j j ƒD]\}}t |j||ƒq Wx3|j j j ƒD]\}}t|j||ƒqΦW|S(shConvert named signatures to object of type SignatureDef. Args: signatures: object of type manifest_pb2.Signatures() Returns: object of type SignatureDef which contains a converted version of named signatures from input signatures object Raises: RuntimeError: if input and output named signatures are not of type GenericSignature Rtgeneric_signatures‘Named input and output signatures can only be up-converted if they are generic signature. Input signature type is %s, output signature type is %s(RRtnamed_signaturesR tPREDICT_INPUTStPREDICT_OUTPUTSRR(tPREDICT_METHOD_NAMERR+tmaptitemsRRR(R)Rtinput_signaturetoutput_signaturetkeytval((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt*_convert_named_signatures_to_signature_defos      cC`s‘|j}tjƒ}|tjjjd}|j|ƒd}d}|j dƒrct |ƒ}nt |j ƒdkr‡t |ƒ}n||fS(sμProduce default and named upconverted SignatureDef objects from Signatures. Args: metagraph_def: object of type meta_graph_pb2.MetaGraphDef containing legacy format Session Bundle signatures Returns: default_signature_def: object of type SignatureDef which contains an upconverted version of default signatures in metagraph_def named_signature_def: object of type SignatureDef which contains an upconverted version of named signatures in metagraph_def iRiN(tcollection_defRt Signaturestlegacy_constantstSIGNATURES_KEYtany_listtvaluetUnpacktNonetHasFieldR*tlenR,R6(t metagraph_defR7tsignatures_protoR)tdefault_signature_deftnamed_signature_def((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt%_convert_signatures_to_signature_defs”s     c C`sΥtjj|tjƒ}tj|ƒ}|jr?tdƒ‚nt |ƒ\}}|rq|jt j j |ƒn|rͺt j }|r“|d7}n|j|j |ƒnt j|||d|ƒ\}}||fS(sTLoad legacy TF Exporter/SessionBundle checkpoint. Args: export_dir: the directory that contains files exported by exporter. target: The execution engine to connect to. See target in tf.Session() config: A ConfigProto proto with configuration options. See config in tf.Session() Returns: session: a tensorflow session created from the variable files. metagraph_def: The `MetaGraphDef` protocol buffer loaded in the provided session. This can be used to further extract signature-defs, collection-defs, etc. This model is up-converted to SavedModel format. Specifically, metagraph_def SignatureDef field is populated with Signatures converted from legacy signatures contained within CollectionDef Raises: RuntimeError: If metagraph already contains signature_def and cannot be up-converted. s:Legacy graph contains signature def, unable to up-convert.t _from_namedtmeta_graph_def(tostpathtjoinR9tMETA_GRAPH_DEF_FILENAMERtread_meta_graph_fileRR(RER t!DEFAULT_SERVING_SIGNATURE_DEF_KEYRRtload_session_bundle_from_path( t export_dirttargettconfigtmeta_graph_filenameRARCRDtsignature_def_keytsess((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt*_load_saved_model_from_session_bundle_path²s$       tcC`s’d}d}tj|ƒrNtj|ddd|ƒ}tj|||ƒ}n:tj|ƒrxt|||ƒ\}}nt d|ƒ‚||fS(s½Load session bundle from the given path. The function reads input from the export_dir, constructs the graph data to the default graph and restores the parameters for the session created. Args: export_dir: the directory that contains files exported by exporter. tags: Set of string tags to identify the required MetaGraphDef when model is saved as SavedModel. These should correspond to the tags used when saving the variables using the SavedModel `save()` API. target: The execution engine to connect to. See target in tf.Session() config: A ConfigProto proto with configuration options. See config in tf.Session() Returns: session: a tensorflow session created from the variable files. meta_graph: a meta graph proto saved in the exporter directory. Raises: RuntimeError: if the required files are missing or contain unrecognizable fields, i.e. the exported model is invalid. tgraphRQsLSessionBundle or SavedModelBundle not found at specified export location: %sN( R>R tmaybe_saved_model_directoryRtSessiontloadRtmaybe_session_bundle_dirRUR((ROttagsRPRQRART((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyt3load_session_bundle_or_saved_model_bundle_from_pathθs (t__doc__t __future__RRRRHt!tensorflow.contrib.session_bundleRR9RRttensorflow.core.protobufRttensorflow.python.clientRttensorflow.python.frameworkRttensorflow.python.saved_modelR R RRR*R6RERUR>R](((so/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/session_bundle/bundle_shim.pyts*    + %  7