B ð»ˆdaã@s€dZddlZej e¡d ej dd¡¡sRddlmZddl m Z ddl m Znddlm Z dd „Zed ƒGd d „d ƒƒZdS) z+This tool analyzes a TensorFlow Lite graph.éNÚtflite_runtimeZanalyzer)Ú wrap_toco)Ú_pywrap_analyzer_wrapper)Ú tf_exportcOs ~~dd„S)NcSs|S)N©)ÚxrrúQ/var/www/html/venv/lib/python3.7/site-packages/tensorflow/lite/python/analyzer.pyÚ óz_tf_export..r)rÚkwargsrrrÚ _tf_exportsr zlite.experimental.Analyzerc@seZdZdZeddd„ƒZdS)Ú ModelAnalyzerupProvides a collection of TFLite model analyzer tools. Example: ```python model = tf.keras.applications.MobileNetV3Large() fb_model = tf.lite.TFLiteConverterV2.from_keras_model(model).convert() tf.lite.experimental.Analyzer.analyze(model_content=fb_model) # === TFLite ModelAnalyzer === # # Your TFLite model has ‘1’ subgraph(s). In the subgraph description below, # T# represents the Tensor numbers. For example, in Subgraph#0, the MUL op # takes tensor #0 and tensor #19 as input and produces tensor #136 as output. # # Subgraph#0 main(T#0) -> [T#263] # Op#0 MUL(T#0, T#19) -> [T#136] # Op#1 ADD(T#136, T#18) -> [T#137] # Op#2 CONV_2D(T#137, T#44, T#93) -> [T#138] # Op#3 HARD_SWISH(T#138) -> [T#139] # Op#4 DEPTHWISE_CONV_2D(T#139, T#94, T#24) -> [T#140] # ... ``` WARNING: Experimental interface, subject to change. NFcKsr|s|stdƒ‚|r.td|›dƒ|}d}ntdƒ|}d}| dd¡r\tt ||¡ƒntt |||¡ƒdS) aãAnalyzes the given tflite_model with dumping model structure. This tool provides a way to understand users' TFLite flatbuffer model by dumping internal graph structure. It also provides additional features like checking GPU delegate compatibility. WARNING: Experimental interface, subject to change. The output format is not guaranteed to stay stable, so don't write scripts to this. Args: model_path: TFLite flatbuffer model path. model_content: TFLite flatbuffer model object. gpu_compatibility: Whether to check GPU delegate compatibility. **kwargs: Experimental keyword arguments to analyze API. Returns: Print analyzed report via console output. z4neither `model_path` nor `model_content` is providedz=== z === Tz=== TFLite ModelAnalyzer === FZexperimental_use_mlirN)Ú ValueErrorÚprintÚgetrZ wrapped_flat_buffer_file_to_mlirÚ_analyzer_wrapperr )Z model_pathZ model_contentZgpu_compatibilityr Z tflite_modelZinput_is_filepathrrrÚanalyze?s   zModelAnalyzer.analyze)NNF)Ú__name__Ú __module__Ú __qualname__Ú__doc__Ú staticmethodrrrrrr #s r )rÚosÚpathÚsplitextÚ__file__ÚendswithÚjoinZtensorflow.lite.pythonrZ'tensorflow.lite.python.analyzer_wrapperrrZ tensorflow.python.util.tf_exportrr rr rrrrÚs