o Ơi@sUddlmZddlmZmZmZmZmZddlZ ddl Z ddl Z ddl mZddlmZddlmZddlmZmZddlmZd d lmZmZGd d d eZe jeje jeje jeje jie j eje j eje j eje j ie j!eje j!eje j!eje j!ie j"eje j"eje j"eje j"ie j#eje j#eje j#eje j#ie j$eje$eje j$eje j$iiZ%eeeeeee j&e j&fffe'd <e j(dkreje j)eje j$eje j$ie%e j$<GdddeZ*deee j&e j&fdedee j&e j&effddZ+dedee,fddZ-ddZ.dde/fddZ0dS) )Enum)CallableDictListOptionalUnionN)make_fx) functionalize)sanitized_torch_version)replace_op_with_indicesrun_const_fold)version)Shape TRTDataTypec@seZdZdZdZdZdS) FrameworksnumpytorchtrtN)__name__ __module__ __qualname__NUMPYTORCHTRTrrK/home/ubuntu/.local/lib/python3.10/site-packages/torch_tensorrt/fx/utils.pyrsrDataTypeEquivalencez7.0c@s6eZdZdZdZdZdZedede dfddZ d S) LowerPrecisionfp32fp16int8bf16labelreturncCs<|dvrtjS|dvrtjS|dvrtjS|dvrtjSdS)N)rfloat32floatz torch.float32)r float16halfz torch.halfz torch.float16r!)r"bfloat16ztorch.bfloat16)rFP32FP16INT8BF16)r#rrrfrom_strMszLowerPrecision.from_strN) rrrr*r+r,r- staticmethodstrrr.rrrrrGsrdtypetor$cCs |tvs Jd|ttjdd}|tjtjtjfvr&ttj|S|dkr;|tj tj tj fvr;ttj |S|tj tj tj fvrLttj |S|tj tj tj fvr]ttj |S|tj tj tj fvrnttj |S|tjtjtjfvrttj|Std|)aM Convert TensorRT, Numpy, or Torch data types to any other of those data types. Args: dtype (TRTDataType, torch.dtype, np.dtype): A TensorRT, Numpy, or Torch data type. to (Frameworks): The framework to convert the data type to. Returns: The equivalent data type in the requested framework. z.Expected valid Framework for translation, got .rz%s is not a supported dtype)rintr __version__splitnpr!rrbool_boolint32int64r'r% TypeError)r1r2trt_major_versionrrrunified_dtype_converter[s  r?shapecCs,g}t|D] \}}|dkr||q|S)aB This function finds the dynamic dimensions in the given shape. A dimension is dynamic if it's -1. Args: shape (Shape): A sequence of integer that represents the shape of a tensor. Returns: A list of integers contains all the dynamic dimensions in the given shape ) enumerateappend)r@ dynamic_dimsisrrrget_dynamic_dimszs   rGcsBfdd}tt||jttS)Ncs|S)Nr)inpmodrrfszproxytensor_trace..f)evalrr grapheliminate_dead_coder r )rJinputsrKrrIrproxytensor_traces  rP2.devmin_torch_versioncsdtffdd }|S)ak Create a decorator which verifies the Torch version installed against a specified version range Args: min_torch_version (str): The minimum required Torch version for the decorated function to work properly Returns: A decorator which raises a descriptive error message if an unsupported Torch version is used rKcsfdd}|S)NcsNt}tt}||kr tddddtj|i|S)NzExpected Torch version z or greater, z when calling z. Detected version )r parser AssertionErrorrr6)argskwargs min_versioncurrent_version)rKrRrrfunction_wrappers   zEreq_torch_version..nested_decorator..function_wrapperr)rKrYrR)rKrnested_decorators z+req_torch_version..nested_decorator)r)rRr[rrZrreq_torch_versionsr\)rQ)1enumrtypingrrrrrrr8tensorrtrr functorchrfunctorch.experimentalr torch_tensorrt._utilsr )torch_tensorrt.fx.passes.lower_basic_passr r packagingr typesrrrr!rrrr;r<r'r%r:rr1__annotations__r6r9rr?r5rGrPr0r\rrrrs|      #