SYMBOL INDEX (106 symbols across 16 files)

FILE: .github/collect_env.py
  class SystemEnv (line 40) | class SystemEnv(NamedTuple):
  function run (line 52) | def run(command):
  function run_and_read_all (line 64) | def run_and_read_all(run_lambda, command):
  function run_and_parse_first_match (line 72) | def run_and_parse_first_match(run_lambda, command, regex):
  function get_nvidia_driver_version (line 83) | def get_nvidia_driver_version(run_lambda):
  function get_gpu_info (line 91) | def get_gpu_info(run_lambda):
  function get_running_cuda_version (line 105) | def get_running_cuda_version(run_lambda):
  function get_cudnn_version (line 109) | def get_cudnn_version(run_lambda):
  function get_nvidia_smi (line 143) | def get_nvidia_smi():
  function get_platform (line 159) | def get_platform():
  function get_mac_version (line 171) | def get_mac_version(run_lambda):
  function get_windows_version (line 175) | def get_windows_version(run_lambda):
  function get_lsb_version (line 179) | def get_lsb_version(run_lambda):
  function check_release_file (line 183) | def check_release_file(run_lambda):
  function get_os (line 187) | def get_os(run_lambda):
  function get_env_info (line 216) | def get_env_info():
  function pretty_str (line 255) | def pretty_str(envinfo):
  function get_pretty_env_info (line 303) | def get_pretty_env_info():
  function main (line 312) | def main():

FILE: .github/verify_labels.py
  function query_repo (line 47) | def query_repo(cmd: str, *, accept) -> Any:
  function get_pr_merger_and_labels (line 54) | def get_pr_merger_and_labels(pr_number: int) -> Tuple[str, Set[str]]:
  function main (line 62) | def main(args):
  function parse_args (line 69) | def parse_args():

FILE: docs/source/_static/js/custom.js
  function addGithubButton (line 15) | function addGithubButton() {
  function addVersionControl (line 29) | function addVersionControl() {
  function parseGithubButtons (line 95) | function parseGithubButtons (){"use strict";var e=window.document,t=e.lo...
  function onLoad (line 97) | function onLoad() {

FILE: docs/source/conf.py
  function add_ga_javascript (line 111) | def add_ga_javascript(app, pagename, templatename, context, doctree):
  function setup (line 126) | def setup(app):

FILE: scripts/benchmark.py
  function main (line 54) | def main():

FILE: tests/test_crawler.py
  function test_apply (line 11) | def test_apply():
  function test_crawl_module (line 26) | def test_crawl_module():
  function test_summary (line 35) | def test_summary():

FILE: tests/test_modules.py
  class MyModule (line 8) | class MyModule(nn.Module):
    method __init__ (line 9) | def __init__(self):
  function test_module_flops_warning (line 13) | def test_module_flops_warning():
  function test_module_flops (line 53) | def test_module_flops(mod, input_shape, output_shape, expected_val):
  function test_transformer_flops (line 57) | def test_transformer_flops():
  function test_module_macs_warning (line 64) | def test_module_macs_warning():
  function test_module_macs (line 95) | def test_module_macs(mod, input_shape, output_shape, expected_val):
  function test_module_dmas_warning (line 99) | def test_module_dmas_warning():
  function test_module_dmas (line 134) | def test_module_dmas(mod, input_shape, output_shape, expected_val):

FILE: tests/test_process.py
  function test_get_process_gpu_ram (line 8) | def test_get_process_gpu_ram():

FILE: tests/test_utils.py
  function test_format_name (line 6) | def test_format_name():
  function test_wrap_string (line 13) | def test_wrap_string():
  function test_unit_scale (line 35) | def test_unit_scale(input_val, num_val, unit):

FILE: torchscan/crawler.py
  function apply (line 19) | def apply(module: Module, fn: Callable[[Module, str], None], name: Optio...
  function crawl_module (line 34) | def crawl_module(
  function summary (line 268) | def summary(

FILE: torchscan/modules/flops.py
  function module_flops (line 21) | def module_flops(module: Module, inputs: Tuple[Tensor, ...], out: Tensor...
  function flops_linear (line 69) | def flops_linear(module: nn.Linear, inputs: Tuple[Tensor, ...]) -> int:
  function flops_sigmoid (line 79) | def flops_sigmoid(_: nn.Sigmoid, inputs: Tuple[Tensor, ...]) -> int:
  function flops_relu (line 85) | def flops_relu(_: nn.ReLU, inputs: Tuple[Tensor, ...]) -> int:
  function flops_elu (line 91) | def flops_elu(_: nn.ELU, inputs: Tuple[Tensor, ...]) -> int:
  function flops_leakyrelu (line 97) | def flops_leakyrelu(_: nn.LeakyReLU, inputs: Tuple[Tensor, ...]) -> int:
  function flops_relu6 (line 103) | def flops_relu6(_: nn.ReLU6, inputs: Tuple[Tensor, ...]) -> int:
  function flops_tanh (line 109) | def flops_tanh(_: nn.Tanh, inputs: Tuple[Tensor, ...]) -> int:
  function flops_dropout (line 115) | def flops_dropout(module: nn.Dropout, inputs: Tuple[Tensor, ...]) -> int:
  function flops_convtransposend (line 123) | def flops_convtransposend(module: _ConvTransposeNd, inputs: Tuple[Tensor...
  function flops_convnd (line 135) | def flops_convnd(module: _ConvNd, inputs: Tuple[Tensor, ...], out: Tenso...
  function flops_bn (line 151) | def flops_bn(module: _BatchNorm, inputs: Tuple[Tensor, ...]) -> int:
  function flops_maxpool (line 178) | def flops_maxpool(module: _MaxPoolNd, _: Tuple[Tensor, ...], out: Tensor...
  function flops_avgpool (line 186) | def flops_avgpool(module: _AvgPoolNd, inputs: Tuple[Tensor, ...], out: T...
  function flops_adaptive_maxpool (line 194) | def flops_adaptive_maxpool(_: _AdaptiveMaxPoolNd, inputs: Tuple[Tensor, ...
  function flops_adaptive_avgpool (line 206) | def flops_adaptive_avgpool(_: _AdaptiveAvgPoolNd, inputs: Tuple[Tensor, ...
  function flops_layernorm (line 218) | def flops_layernorm(module: nn.LayerNorm, inputs: Tuple[Tensor, ...]) ->...
  function flops_mha (line 234) | def flops_mha(module: nn.MultiheadAttention, inputs: Tuple[Tensor, ...])...
  function flops_transformer_encoderlayer (line 287) | def flops_transformer_encoderlayer(module: nn.TransformerEncoderLayer, i...
  function flops_transformer_decoderlayer (line 304) | def flops_transformer_decoderlayer(module: nn.TransformerDecoderLayer, i...
  function flops_transformer (line 326) | def flops_transformer(module: nn.Transformer, inputs: Tuple[Tensor, ...]...

FILE: torchscan/modules/macs.py
  function module_macs (line 19) | def module_macs(module: Module, inp: Tensor, out: Tensor) -> int:
  function macs_linear (line 53) | def macs_linear(module: nn.Linear, _: Tensor, out: Tensor) -> int:
  function macs_convtransposend (line 59) | def macs_convtransposend(module: _ConvTransposeNd, inp: Tensor, out: Ten...
  function macs_convnd (line 71) | def macs_convnd(module: _ConvNd, inp: Tensor, out: Tensor) -> int:
  function macs_bn (line 84) | def macs_bn(module: _BatchNorm, inp: Tensor, _: Tensor) -> int:
  function macs_maxpool (line 111) | def macs_maxpool(module: _MaxPoolNd, _: Tensor, out: Tensor) -> int:
  function macs_avgpool (line 119) | def macs_avgpool(module: _AvgPoolNd, inp: Tensor, out: Tensor) -> int:
  function macs_adaptive_maxpool (line 127) | def macs_adaptive_maxpool(_: _AdaptiveMaxPoolNd, inp: Tensor, out: Tenso...
  function macs_adaptive_avgpool (line 139) | def macs_adaptive_avgpool(_: _AdaptiveAvgPoolNd, inp: Tensor, out: Tenso...

FILE: torchscan/modules/memory.py
  function module_dmas (line 20) | def module_dmas(module: Module, inp: Tensor, out: Tensor) -> int:
  function num_params (line 61) | def num_params(module: Module) -> int:
  function dmas_identity (line 72) | def dmas_identity(_: nn.Identity, inp: Tensor, __: Tensor) -> int:
  function dmas_flatten (line 77) | def dmas_flatten(_: nn.Flatten, inp: Tensor, __: Tensor) -> int:
  function dmas_linear (line 82) | def dmas_linear(module: nn.Linear, inp: Tensor, out: Tensor) -> int:
  function dmas_relu (line 92) | def dmas_relu(module: Union[nn.ReLU, nn.ReLU6], inp: Tensor, out: Tensor...
  function dmas_act_single_param (line 100) | def dmas_act_single_param(module: Union[nn.ELU, nn.LeakyReLU], inp: Tens...
  function dmas_sigmoid (line 110) | def dmas_sigmoid(_: nn.Sigmoid, inp: Tensor, out: Tensor) -> int:
  function dmas_tanh (line 119) | def dmas_tanh(_: nn.Tanh, inp: Tensor, out: Tensor) -> int:
  function dmas_dropout (line 128) | def dmas_dropout(module: nn.Dropout, inp: Tensor, out: Tensor) -> int:
  function dmas_convtransposend (line 140) | def dmas_convtransposend(module: _ConvTransposeNd, inp: Tensor, out: Ten...
  function dmas_convnd (line 153) | def dmas_convnd(module: _ConvNd, _: Tensor, out: Tensor) -> int:
  function dmas_bn (line 167) | def dmas_bn(module: _BatchNorm, inp: Tensor, out: Tensor) -> int:
  function dmas_pool (line 190) | def dmas_pool(module: Union[_MaxPoolNd, _AvgPoolNd], inp: Tensor, out: T...
  function dmas_adaptive_pool (line 206) | def dmas_adaptive_pool(_: Union[_AdaptiveMaxPoolNd, _AdaptiveAvgPoolNd],...

FILE: torchscan/modules/receptive.py
  function module_rf (line 19) | def module_rf(module: Module, inp: Tensor, out: Tensor) -> Tuple[float, ...
  function rf_convtransposend (line 58) | def rf_convtransposend(module: _ConvTransposeNd, _: Tensor, __: Tensor) ...
  function rf_aggregnd (line 64) | def rf_aggregnd(module: Union[_ConvNd, _MaxPoolNd, _AvgPoolNd], _: Tenso...
  function rf_adaptive_poolnd (line 74) | def rf_adaptive_poolnd(

FILE: torchscan/process/memory.py
  function get_process_gpu_ram (line 15) | def get_process_gpu_ram(pid: int) -> float:

FILE: torchscan/utils.py
  function format_name (line 10) | def format_name(name: str, depth: int = 0) -> str:
  function wrap_string (line 26) | def wrap_string(s: str, max_len: int, delimiter: str = ".", wrap: str = ...
  function unit_scale (line 50) | def unit_scale(val: float) -> Tuple[float, str]:
  function format_s (line 69) | def format_s(f_string: str, min_w: Optional[int] = None, max_w: Optional...
  function format_line_str (line 79) | def format_line_str(
  function format_info (line 109) | def format_info(
  function aggregate_info (line 208) | def aggregate_info(info: Dict[str, Any], max_depth: int) -> Dict[str, Any]: