U <║c╡gу@snddlZddlZddlZddlZddlmZddlmZddlm Z ddl mZddlm Z ddlmZmZddlmZmZmZmZdAeeeed Ьd dДZdd ДZddДZddДZddДZddДZddДZddДZddДZ ddДZ!ddДZ"d d!ДZ#d"d#ДZ$d$d%ДZ%d&d'ДZ&d(d)ДZ'd*d+ДZ(d,d-ДZ)d.d/ДZ*d0d1ДZ+dBd5d6ДZ,d7d8ДZ-d9d:ДZ.d;d<ДZ/dCd=d>ДZ0dDd?d@ДZ1dS)EщN)┌GraphDef)┌NodeDef)┌TensorShapeProto)┌bytes)┌ caffe2_pb2)┌core┌ workspace)┌Set┌Dict┌Tuple┌List)┌seen┌name┌min_versioncCsP|dk stВ|}|r d||fn|}||krB|d7}d||f}q$|а|б|S)a╤ Make the name unique by appending a unique number to the name. Used for SSA. Args: seen (set): Set of names that have already been used (with respect to some context). name (str): The name to make unique min_version (number): Starting index. Is incremented continually until it can make the resulting name unique relative to 'seen'. Returns: x (str): A version of name that is not in seen. Nz%s_%dщ)┌AssertionError┌add)r rr┌i┌xйr·I/tmp/pip-unpacked-wheel-gikjz4vx/torch/utils/tensorboard/_caffe2_graph.py┌_make_unique_names rcsаtаdбЙ tаdбЙ tаdбЙtаdбЙtаdбЙtаdбЙtаdбЙtаdбЙtаd бЙtаd бЙtаdбЙЗЗЗЗЗЗЗЗЗЗ З fdd Д}t||||ГdS)a7 Convert some of the common names in Caffe2 to tensorflow. NOTE: The common names in both Caffe2 and Tensorflow are currently hardcoded, if either side changes at some point, then this code should change as well. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. blob_name_tracker: Dictionary of all unique blob names (with respect to some context). ops: List of Caffe2 operators Returns: None. The _rename_all() call modifies blob_name_tracker and ops in-place. z(_w)$z(_w_)z(_bn)$z(_bn_)z(_b)$z(_b_)z(_s)$z(_s_)z(_sum)$z(_sum_)z (_branch)cstИ аdИ аd|бб}ИаdИаd|бб}ИаdИаd|бб}ИаdИаd|бб}Иаd Иаd |бб}Иаd|б}|S)Nz/weight_z/weightz/batchnorm_z /batchnormz/bias_z/biasz/scale_z/scalez/sum_z/sumz/branch)┌sub)rZ inter_name┌new_nameйZBIASZBIAS_┌BNZBN_┌BRANCHZSCALEZSCALE_ZSUMZSUM_ZWEIGHTZWEIGHT_rr┌fEsz#_rename_tensorflow_style..fN)┌re┌compile┌_rename_allй┌shapes┌blob_name_tracker┌opsrrrr┌_rename_tensorflow_style)s r%cs°tа|б}tГЙiЙiЙiЙttttftdЬЗЗЗЗЗЗfddДЙt||jГD]z\}Й|Иjksft Вt |jГ}t |jГ}|jddЕ=|jddЕ=|jа ЗЗfddД|DГб|jа ЗЗfddД|DГбqPИабИаИбИrЇИабИаИбdS)a╢ Convert an operator graph to SSA (i.e. out-of-place). i.e. blobs will be renamed so that each blob is produced only once. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. blob_name_tracker: Dictionary of all unique blob names (with respect to some context). ops: List of Caffe2 operators Returns: None. Modifies blob_name_tracker and ops in-place. )r┌versions┌returncsv||kstВ||}||fИkr,И||fStИ||dН}|И||f<|ИkrZИ|И|<Иrr|ИkrrИ|И|<|S)N)r)rr)rr&┌versionr)r#┌new_blob_name_tracker┌ new_shapesr r"┌ versionedrr┌ssa_nameesz!_convert_to_ssa..ssa_nameNc3s|]}И|ИjГVqdSйN)Zin_versionsй┌.0rй┌ssar,rr┌ }sz"_convert_to_ssa..c3s|]}И|ИjГVqdSr-)Zout_versionsr.r0rrr2~s)rZIR┌set┌strr ┌int┌zipr1┌opr┌list┌input┌output┌extend┌clear┌update)r"r#r$Zirr7┌inputs┌outputsr)r#r)r*r r"r1r,r+r┌_convert_to_ssaQs& ( r@cCs6tГ}|D]}|а|jб|а|jбq ddД|DГS)zў Get all the operator input and output blobs and perform dedup on their names. Args: ops: List of Caffe2 operators to extract inputs and outputs from Returns: set containing distinct inputs and outputs from 'ops' cSsi|] }||УqSrrr.rrr┌ Хsz#_get_blob_names..)r3r=r9r:)r$┌namesr7rrr┌_get_blob_namesЗs rCcs,ЗfddД|абDГ}|аб|а|бdS)a Rename keys of 'old_dict' according to 'rename_fn'. Args: old_dict: Dictionary (i.e. containing blob_name -> blob_name relationships.) remap_fn: Function string -> string for renaming. Returns: None. Modifies old_dict in-place. csi|]\}}И|Г|УqSrr)r/┌key┌valueй┌ rename_fnrrrAдsz_remap_keys..N)┌itemsr<r=)Zold_dictrGZnew_dictrrFr┌_remap_keysШsrIcs╞tГЙiЙЗЗЗfddДЙ|D]d}t|jГ}t|jГ}|jddЕ=|jddЕ=|jаЗfddД|DГб|jаЗfddД|DГбqt|ИГ|rЬt|ИГИабИаб|D]}И|jГ|_q░dS)a▌ Rename all the names in the operators. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. blob_name_tracker: Dictionary of all unique blob names (with respect to some context). ops: List of Caffe2 operators rename_fn: Function string -> string that specifies how to rename Returns: None. Modifies shapes, blob_name_tracker and ops in-place using the specified 'rename_fn'. cs6|dkrdS|ИkrИ|StИИ|ГГ}|И|<|S)zCollision-free version of f.N)r)rr)rG┌renamedr rr┌g╗sz_rename_all..gNc3s|]}И|ГVqdSr-rr.йrKrrr2╩sz_rename_all..c3s|]}И|ГVqdSr-rr.rLrrr2╦s)r3r8r9r:r;rIr<r)r"r#r$rGr7r>r?r)rKrGrJr rr йs" r cCsddД}t||||ГdS)a∙ For all operators or blobs with name containing "_grad", add a "GRADIENTS/" scope. Note: breaks graph execution since the blob -> gradient mapping is hardcoded. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. blob_name_tracker: Dictionary of all unique blob names (with respect to some context). ops: List of Caffe2 operators Returns: None. Modifies shapes, blob_name_tracker and ops in-place by renaming. cSsd|krdа|бS|SdS)NZ_gradzGRADIENTS/{})┌formatйrrrrrщs z_add_gradient_scope..fNйr r!rrr┌_add_gradient_scope╪srPcsЗfddД}t||||ГdS)a `:i` has a special meaning in Tensorflow. This function replaces all colons with $ to avoid any possible conflicts. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. blob_name_tracker: Dictionary of all unique blob names (with respect to some context). ops: List of Caffe2 operators repl: String representing the text to replace ':' with. Usually this is '$'. Returns: None. Modifies blob_name_tracker in-place. cs|аdИбS)N·:)┌replacerNй┌replrrrsz_replace_colons..fNrO)r"r#r$rTrrrSr┌_replace_colonsЄsrUcCsЮtГ}|D]}|а|jб|а|jбq |D]l}|jr>|j}nF|jsJ|jr~ddД|jpZ|jDГ}tjа|б}tjа||j б}n|j }|sМt Вt||Г|_q,dS)a[ Give missing operators a name. We expect C2 operators to be generally unnamed. This gives them a scope (inferred from their outputs) and a name after their type. Duplicates will be postfixed by an index. Args: ops: List of Caffe2 operators to assign names to. Returns: None: Modifies 'ops' in-place. cSsg|]}tjа|бСqSr)┌os┌path┌dirnamer.rrr┌ sz0_fill_missing_operator_names..N)r3r=r9r:rrVrW┌commonprefix┌join┌typerr)r$r r7r┌ name_list┌scoperrr┌_fill_missing_operator_names s r_cCsP|аdбsdS|jtjks&|jtjkr*dS|jtjkrBdа|jбStd|ГВdS)aў Handle the devices. Args: device_option (caffe2_pb2.DeviceOption): DeviceOption protobuf, associated to an operator, that contains information such as device_type (optional), cuda_gpu_id (optional), node_name (optional, tells which node the operator should execute on). See caffe2.proto in caffe2/proto for the full list. Returns: Formatted string representing device information contained in device_option. ┌device_type┌z/cpu:*z/gpu:{}zUnhandled deviceN) ┌HasFieldr`rZCPUZMKLDNNZCUDArMZ device_id┌ Exceptionй┌ device_optionrrr┌ _tf_device)s ■rfcCsDtГ}|D] }tаб}||_|jа|gбq |djjа|gбdS)a; Converts a list of ints to a TensorShapeProto representing the dimensions of a blob/object. Args: attr_dict: Dictionary to update (usually attributes of a Node) ints: List of integers representing dimensions of some object. Returns: None. Modifies attr_dict in-place. Z_output_shapesN)rZDim┌size┌dimr;r8┌shape)┌ attr_dict┌intsZshape_protorrhrrr┌ _add_tf_shapeDsrlcCs|j}|dkr$|jr$t||jГdS|аdбr>|j||_dS|аdбrX|j||_dS|аdбrОt|jtГrt|jnt |jГа dб||_dS|jrм||jjа |jбdS|jr╩||jjа |jбdS|jrЄ||jjа ddД|jDГбdS||jjа gбdS) a; Add attributes to a node. Key is the arg.name, and values can be shape, floats, strings, ints or an empty list. Args: attr_dict: Dictionary to update (usually attributes of a Node) arg: Object with name and data fields. Returns: None. Modifies attr_dict in-place. riNrr┌s·utf-8css*|]"}t|tГr|nt|ГаdбVqdS)rnN)┌ isinstancerr4┌encode)r/rmrrrr2}sz_set_tf_attr..)rrkrlrbrrrormrr4rpZfloatsr8r;┌strings)rj┌arg┌krrr┌_set_tf_attrXs4 rtcCsЖ|jst|ГВtГ}|j|_|jа|jб|j|_t|jГ|_ |rj|j D] }||krXqjt|j||ГqH|j D]}t|j|Гqp|S)a Converts an operator to a node in a TF graph. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. op: The Caffe2 operator to convert to a TF graph node. Returns: n: The TF graph node created from op. )rrrr9r;r\r7rfre┌devicer:rl┌attrrrrt)r"r7┌nr:rrrrr┌_operator_to_nodeЕs rxc sx|stВg}ЗfddД|jDГ}|а|бt|Г}|dkrРtГ}|d|_|jа|jб|j|_ t |jГ|_|j D]}t|j|Гqr|а|бnф|dkРrt|jrи|j}n$t|Г} tjа| б} tjа| |jб}|s╘tВt||Г|_t |jГ}|D]6}tГ}||_|jа|jgбd|_ ||_|а|бqюtГ}|j|_|jа|jб|j|_ ||_|j D]}t|j|ГРqV|а|б|S)a" Convert the operators to nodes. Args: op: Caffe2 operator to convert to node inter_blobs: Set of intermediate blobs seen: Names that have already been used and are not unique Returns: nodes: Nodes representing 'op' and the outputs of 'op' csg|]}|Иkr|СqSrrйr/┌oй┌inter_blobsrrrYпsz*_operator_to_node_simp..rr┌Blob)rr:r=┌lenrrr9r;r\r7rfrerurrrtrv┌appendr8rVrWrZr[r) r7r|r Znodesr?Zlen_outputsrwrrrr]r^rur:rr{r┌_operator_to_node_simpбsN rАcsв|stВtГ}||_|а|gб}t|Гdkr4d|_nd|_|jаddД|DГб|rВ|ddjЙt ЗfddД|DГГrВt ИГ|_|rЮ||krЮt|j ||Г|S)aг Converts a blob (operator input or output) to a node in a TF graph. Args: producing_ops: Dictionary of blob name to list of (producing_op, blob_index within producing_op.output) mapping. shapes: Dictionary mapping blob names to their shapes/dimensions. name: String representing the name of this blob. Returns: n: The TF graph node created from this blob. rr}ZPlaceholdercss |]\}}d|j|fVqdS)z%s:%dNrN)r/Zp_oprrrrr2ўsz _blob_to_node..c3s|]}|djИkVqdS)rNrd)r/Zproducerйrurrr2·s)rrr┌getr~r7r9r;re┌allrfrurlrv)┌ producing_opsr"rrwZproduced_byrrБr┌ _blob_to_node▐s rЕcCs*|sdS|D]}|аdбr|аdбqdS)a▄ Removes debug information from operators, they are copious. Args: ops: List of Caffe2 operators perform_clear: Boolean passed from _operators_to_graph_def specifying whether to remove the debug information. This boolean is passed into this function to reduce the complexity of _operators_to_graph_def. Returns: None. Modifies the list of Caffe2 operators in-place and removes the 'debug_info' field. NZ debug_info)rbZ ClearField)r$Z perform_clearr7rrr┌_clear_debug_infos rЖcCs|аdбdkp|аdбdkS)a- Blobs with names containing '_m' or 'grad' are part of the backward pass. This function references facebookresearch/Detectron/detectron/utils/net.py. Args: blob: The blob to inspect Returns: Boolean representing whether this blob is part of the forward pass Z__mrZgrad)┌findй┌blobrrr┌_check_if_forwardsrКcCs|аdбS)z╣ Check if the blob's name starts with '_gpu'. Args: blob: The blob to inspect Returns: Boolean representing whether this blob is associated with a gpu Z_gpuй┌ startswithrИrrr┌ _check_if_cpu's rНcsИtГ}tГ}|D]0}|jD]}|а|бq|jD]}|а|бq0qt|а|бГ}t|а|бГ}ddД|DГЙЗfddД|DГ}|И|fS)a] Find the input, intermediate and output nodes of a set of operators. Args: ops: List of Caffe2 operators to look through Returns: input_blobs: The input nodes of the set of operators inter_blobs: The intermediate nodes of the set of operators output_blobs: The output nodes of the set of operators cSsh|]}|аdбr|ТqS)┌_rЛйr/┌brrr┌ Ks z"_compute_in_out..csg|]}|Иkr|СqSrrrПr{rrrYLsz#_compute_in_out..)r3r9rr:r8┌ difference)r$Zin_blobsZ out_blobsr7┌ input_blob┌output_blob┌input_blobsZoutput_blobsrr{r┌_compute_in_out4s rЦc sР|s|Sg}|D]z}t|jГ}t|jГ}|jddЕ=|jddЕ=ЗfddД|DГ}ЗfddД|DГ}|r|jа|б|jа|б|а|бq|S)a─ Filter unwanted operators based on criteria in 'filter_fn'. Args: ops: List of Caffe2 operators to filter filter_fn: Criteria function for whether inputs/outputs in an operator should be filtered. perform_filter: Boolean passed from _operators_to_graph_def specifying whether to filter operators Returns: new_ops: Subset of ops containing a subset of their inputs and outputs. Ncsg|]}И|Гr|СqSrr)r/rй┌ filter_fnrrrYhsz_filter_ops..csg|]}И|Гr|СqSrrryrЧrrrYis)r8r9r:r;r) r$rШZperform_filterZnew_opsr7r>r?Z new_inputsZnew_outputsrrЧr┌_filter_opsQs rЩ·$TFcCsz|dk r|абni}|аt|Гбt||Гt|t|Г}t|t|Г}|rXt||||Г|rjt||||Г|rzt |||Г|rКt |||Гt|Г|rвt|||Гi}t Г} t|Г\} }}tГ} t | Г}|D]x}|rрt|||Гn t||Гg}| jа|б|jD]}| а|бq■t|jГD]*\}}| а|б|а|gба||fбРqq╠|РrP| } t| ГD]}| jаt|i|ГgбРqX| S)a1 Main function to convert set of operators to a graph. Args: shapes: Dictionary mapping blob names to their shapes/dimensions. ops: List of Caffe2 operators, representing some computation graph ### **kwargs (model_to_graph_def, nets_to_graph_def, protos_to_graph_def) ### colon_replacement: Symbol to replace ':' with. ':i' in TF has a special meaning, so we need to replace it with a non-conflicting symbol. with_ssa: Boolean with_gradient_scope: Boolean blob_name_tracker: Dictionary tracking names of blobs (inputs/outputs from operators) show_simplified: Whether to show a simplified version of the model graph Sets all of the following values: clear_debug_info: Boolean representing whether to silence debug info (which can be very verbose) show_forward_only: Boolean representing whether to only show blobs involved in the forward pass show_cpu_only: Boolean representing whether to only show blobs that are not associated with a gpu use_tensorflow_naming: Boolean representing whether to convert some common Caffe2 naming conventions to their Tensorflow counterparts custom_rename: Function string -> string that defines a custom renaming function to use. Returns: current_graph: GraphDef representing the computation graph formed by the set of operators. N)r<r=rCrЖrЩrКrНr rUr@rPr_r%r3rЦrrАrx┌noder;r9r┌ enumerater:┌ setdefaultr┌sortedrЕ)r"r$Zcolon_replacementZwith_ssaZwith_gradient_scoper#Zshow_simplifiedZ custom_renamerДZblobsrХr|rОZ current_graphr r7Z nodes_from_oprУrrФrЙrrr┌_operators_to_graph_deftsN) ¤ rЯcCs6|аdбsdS|jD]}|аdбs|jа|jбqdS)aю Propagate the device options from net to operators. Args: net_def: A caffe2_pb2.NetDef representing a computation graph. The graph consists of Caffe2 operators. Returns: None. Iterates through all ops contained within the net. For each op, modifies the op device_option in-place to be the net device_option if the op has no pre-existing device_option, and leaves the op as-is if it already has a device_option. reN)rbr7reZCopyFrom)┌net_defr7rrr┌_propagate_device_option╬s rбc CsPztа|б\}}|WStk rJ}ztаd|бiWYвSd}~XYnXdS)aЕ Get missing shapes for all blobs contained in the nets. Args: nets: List of core.Net to extract blob shape information from. Returns: Dictionary containing blob name to shape/dimensions mapping. The net is a computation graph that is composed of operators, and the operators have input and output blobs, each with their own dims. zFailed to compute shapes: %sN)rZInferShapesAndTypesrc┌logging┌warning)┌netsr"rО┌errr┌_try_get_shapesуsrжcKs|j|jg}t|f|ОS)aЁ Convert a Caffe2 model to a Tensorflow graph. This function extracts 'param_init_net' and 'net' from the model and passes it to nets_to_graph() for further processing. Args: model (cnn.CNNModelHelper, model_helper.ModelHelper): The model to extract the nets (instances of core.Net) from. Returns: Call to nets_to_graph_def() with extracted 'param_init_net', 'net' and **kwargs. See _operators_to_graph_def for detailed **kwargs. )Zparam_init_net┌net┌nets_to_graph_def)┌model┌kwargsrдrrr┌model_to_graph_def∙srлcKs*i}ddД|DГ}tа|б}t||f|ОS)a╨ Convert a set of Caffe2 nets to a Tensorflow graph. Args: nets: List of core.Nets. core.Net is a wrapper around a NetDef protobuf. The corresponding protobuf can be extracted using .Proto(). shapes: Dictionary mapping blob names to their shapes/dimensions. Returns: Call to protos_to_graph_def() with the extracted NetDef protobufs and **kwargs. See _operators_to_graph_def for detailed **kwargs. cSsg|]}tа|аббСqSr)┌copy┌deepcopyZProto)r/rзrrrrYsz%nets_to_graph_def..)rмrн┌protos_to_graph_def)rдr"rкrrrrиs rиcKs<|D]}t|Гqtа|piб}ddД|DГ}t||f|ОS)a┐ Convert a set of Caffe2 net definitions to a Tensorflow graph. Args: net_defs: List of caffe2_pb2.NetDef protobufs representing computation graphs. shapes: Dictionary mapping blob names to their shapes/dimensions. Returns: Call to _operators_to_graph_def() with the extracted operators from the NetDefs and **kwargs. See _operators_to_graph_def for detailed **kwargs. cSsg|]}|jD]}|СqqSr)r7)r/rаr7rrrrY3sz'protos_to_graph_def..)rбrмrнrЯ)Znet_defsr"rкrзr$rrrrо"s rо)r)rЪTTNFN)N)N)2rмrвrVrZ"tensorboard.compat.proto.graph_pb2rZ%tensorboard.compat.proto.node_def_pb2rZ)tensorboard.compat.proto.tensor_shape_pb2r┌builtinsrZcaffe2.protorZ caffe2.pythonrr┌typingr r rrr4r5rr%r@rCrIr rPrUr_rfrlrtrxrАrЕrЖrКrНrЦrЩrЯrбrжrлrиrоrrrr┌sT(6/-=# &° Z