SYMBOL INDEX (23 symbols across 4 files)

FILE: clip_onnx/benchmark.py
  function speed_test (line 5) | def speed_test(func, data_gen, n: int = 5, empty_cache: bool = True):

FILE: clip_onnx/clip_converter.py
  class clip_converter (line 8) | class clip_converter(nn.Module):
    method __init__ (line 9) | def __init__(self, model, visual_path: str = "clip_visual.onnx",
    method quantization (line 23) | def quantization(self, mode: str = "dynamic"):
    method torch_export (line 38) | def torch_export(self, model, dummy_input, path: str, export_params=DE...
    method onnx_checker (line 41) | def onnx_checker(self, path: str):
    method convert_visual (line 46) | def convert_visual(self, dummy_input, wrapper=lambda x: x,
    method convert_textual (line 53) | def convert_textual(self, dummy_input, wrapper=Textual,
    method convert2onnx (line 60) | def convert2onnx(self, visual_input=None, textual_input=None, verbose=...

FILE: clip_onnx/clip_onnx.py
  class clip_onnx (line 6) | class clip_onnx(clip_converter):
    method __init__ (line 7) | def __init__(self, model=None,
    method load_onnx (line 15) | def load_onnx(self, visual_path=None, textual_path=None, logit_scale=N...
    method start_sessions (line 27) | def start_sessions(self, providers=['TensorrtExecutionProvider',
    method visual_run (line 37) | def visual_run(self, onnx_image):
    method textual_run (line 42) | def textual_run(self, onnx_text):
    method __call__ (line 47) | def __call__(self, image, text, device: str = "cpu"):
    method encode_image (line 63) | def encode_image(self, image):
    method encode_text (line 66) | def encode_text(self, text):

FILE: clip_onnx/utils.py
  class Textual (line 6) | class Textual(nn.Module):
    method __init__ (line 7) | def __init__(self, model):
    method forward (line 16) | def forward(self, text):
  function attention (line 33) | def attention(self, x: torch.Tensor):
  function scaled_dot_product_attention (line 51) | def scaled_dot_product_attention(Q, K, V, attn_mask, dropout_p):