SYMBOL INDEX (274 symbols across 59 files)

FILE: github_adventures/automata/model.py
  class CAModel (line 5) | class CAModel(nn.Module):
    method __init__ (line 32) | def __init__(self, n_channels=16, hidden_channels=128, fire_rate=0.5, ...
    method perceive (line 83) | def perceive(self, x):
    method update (line 102) | def update(self, x):
    method stochastic_update (line 121) | def stochastic_update(x, fire_rate):
    method get_living_mask (line 146) | def get_living_mask(x):
    method forward (line 167) | def forward(self, x):

FILE: github_adventures/automata/train.py
  function load_image (line 14) | def load_image(path, size=40):
  function to_rgb (line 40) | def to_rgb(img_rgba):
  function make_seed (line 58) | def make_seed(size, n_channels):
  function main (line 82) | def main(argv=None):

FILE: github_adventures/diffaugment/script.py
  function main (line 17) | def main(argv=None):

FILE: github_adventures/diffaugment/utils.py
  class DatasetImages (line 6) | class DatasetImages(Dataset):
    method __init__ (line 22) | def __init__(self, path, transform=None):
    method __len__ (line 28) | def __len__(self):
    method __getitem__ (line 32) | def __getitem__(self, ix):
  class Generator (line 43) | class Generator(nn.Module):
    method __init__ (line 63) | def __init__(self, latent_dim, ngf=64):
    method forward (line 91) | def forward(self, x):
  class Discriminator (line 108) | class Discriminator(nn.Module):
    method __init__ (line 128) | def __init__(self, ndf=16, augment_module=None):
    method forward (line 161) | def forward(self, x):
  function init_weights_ (line 182) | def init_weights_(module):

FILE: github_adventures/dino/evaluation.py
  function compute_knn (line 7) | def compute_knn(backbone, data_loader_train, data_loader_val):
  function compute_embedding (line 57) | def compute_embedding(backbone, data_loader):

FILE: github_adventures/dino/train.py
  function main (line 17) | def main():

FILE: github_adventures/dino/utils.py
  class DataAugmentation (line 8) | class DataAugmentation:
    method __init__ (line 36) | def __init__(
    method __call__ (line 113) | def __call__(self, img):
  class Head (line 136) | class Head(nn.Module):
    method __init__ (line 173) | def __init__(
    method _init_weights (line 203) | def _init_weights(self, m):
    method forward (line 210) | def forward(self, x):
  class MultiCropWrapper (line 230) | class MultiCropWrapper(nn.Module):
    method __init__ (line 242) | def __init__(self, backbone, new_head):
    method forward (line 248) | def forward(self, x):
  class Loss (line 275) | class Loss(nn.Module):
    method __init__ (line 293) | def __init__(
    method forward (line 302) | def forward(self, student_output, teacher_output):
    method update_center (line 342) | def update_center(self, teacher_output):
  function clip_gradients (line 360) | def clip_gradients(model, clip=2.0):

FILE: github_adventures/gpt/copy_and_generate.py
  function main (line 14) | def main(argv=None):

FILE: github_adventures/gpt/model.py
  class CustomGELU (line 7) | class CustomGELU(nn.Module):
    method forward (line 10) | def forward(self, x):
  class Block (line 15) | class Block(nn.Module):
    method __init__ (line 51) | def __init__(
    method forward (line 87) | def forward(self, x):
  class GPT (line 115) | class GPT(nn.Module):
    method __init__ (line 168) | def __init__(
    method forward (line 204) | def forward(self, idx):

FILE: github_adventures/gpt/utils.py
  function copy_parameter (line 4) | def copy_parameter(param_official, param_ours):
  function copy_block (line 23) | def copy_block(block_official, block_ours):
  function copy_model (line 60) | def copy_model(model_official, model_ours):
  function generate_token (line 89) | def generate_token(

FILE: github_adventures/integer/bert.py
  function main (line 11) | def main(argv=None):

FILE: github_adventures/integer/fetch_data.py
  function get_sequence (line 9) | def get_sequence(sequence_id):

FILE: github_adventures/integer/glove.py
  function main (line 9) | def main(argv=None):

FILE: github_adventures/integer/lstm.py
  function main (line 22) | def main(argv=None):

FILE: github_adventures/integer/utils.py
  class CustomDataset (line 12) | class CustomDataset(Dataset):
    method __init__ (line 39) | def __init__(
    method __len__ (line 65) | def __len__(self):
    method __getitem__ (line 69) | def __getitem__(self, ix):
  class Network (line 74) | class Network(nn.Module):
    method __init__ (line 112) | def __init__(
    method forward (line 145) | def forward(self, x):
  function train_classifier (line 172) | def train_classifier(X, y, random_state=2):
  function create_classification_targets (line 221) | def create_classification_targets(indices):

FILE: github_adventures/lottery/data.py
  class MNISTDataset (line 6) | class MNISTDataset(Dataset):
    method __init__ (line 26) | def __init__(self, root, train=True, download=True):
    method __len__ (line 41) | def __len__(self):
    method __getitem__ (line 45) | def __getitem__(self, ix):

FILE: github_adventures/lottery/main.py
  function loop_dataloader (line 13) | def loop_dataloader(dataloader):
  function train (line 34) | def train(
  function main (line 103) | def main(argv=None):

FILE: github_adventures/lottery/utils.py
  class MLP (line 8) | class MLP(nn.Module):
    method __init__ (line 30) | def __init__(self, n_features, hidden_layer_sizes, n_targets):
    method forward (line 41) | def forward(self, x):
  function prune_linear (line 65) | def prune_linear(linear, prune_ratio=0.3, method="l1"):
  function prune_mlp (line 94) | def prune_mlp(mlp, prune_ratio=0.3, method="l1"):
  function check_pruned_linear (line 127) | def check_pruned_linear(linear):
  function reinit_linear (line 148) | def reinit_linear(linear):
  function reinit_mlp (line 180) | def reinit_mlp(mlp):
  function copy_weights_linear (line 192) | def copy_weights_linear(linear_unpruned, linear_pruned):
  function copy_weights_mlp (line 213) | def copy_weights_mlp(mlp_unpruned, mlp_pruned):
  function compute_stats (line 232) | def compute_stats(mlp):

FILE: github_adventures/mixer/official.py
  class MlpBlock (line 6) | class MlpBlock(nn.Module):
    method __call__ (line 10) | def __call__(self, x):
  class MixerBlock (line 16) | class MixerBlock(nn.Module):
    method __call__ (line 21) | def __call__(self, x):
  class MlpMixer (line 31) | class MlpMixer(nn.Module):
    method __call__ (line 40) | def __call__(self, x):

FILE: github_adventures/mixer/ours.py
  class MlpBlock (line 5) | class MlpBlock(nn.Module):
    method __init__ (line 26) | def __init__(self, dim, mlp_dim=None):
    method forward (line 34) | def forward(self, x):
  class MixerBlock (line 54) | class MixerBlock(nn.Module):
    method __init__ (line 83) | def __init__(
    method forward (line 94) | def forward(self, x):
  class MlpMixer (line 120) | class MlpMixer(nn.Module):
    method __init__ (line 162) | def __init__(
    method forward (line 197) | def forward(self, x):

FILE: github_adventures/mixer/test_compare.py
  function test_compare (line 17) | def test_compare(

FILE: github_adventures/mixup/train.py
  function main (line 18) | def main(argv=None):

FILE: github_adventures/mixup/utils.py
  class MLPClassifierMixup (line 9) | class MLPClassifierMixup(nn.Module):
    method __init__ (line 38) | def __init__(self, n_features, hidden_dims, p=0):
    method forward (line 55) | def forward(self, x, start=0, end=None):
  class CustomDataset (line 82) | class CustomDataset(Dataset):
    method __init__ (line 94) | def __init__(self, X, y):
    method __len__ (line 105) | def __len__(self):
    method __getitem__ (line 109) | def __getitem__(self, ix):
  function generate_spirals (line 114) | def generate_spirals(
  function generate_prediction_img (line 184) | def generate_prediction_img(

FILE: github_adventures/ner_evaluation/ours.py
  function check_valid (line 6) | def check_valid(annots: list[str]) -> bool:
  function get_etypes (line 25) | def get_etypes(annots: list[str]) -> list[None | str]:
  function get_entities (line 29) | def get_entities(annots: list[str]) -> list[dict[str, int | str]]:
  function get_report (line 81) | def get_report(annots_true: list[str], annots_pred: list[str]) -> dict:

FILE: github_adventures/ner_evaluation/test_ours.py
  function test_check_valid (line 23) | def test_check_valid(inp, out):
  function test_get_etypes (line 38) | def test_get_etypes(inp, out):
  function test_get_entities (line 72) | def test_get_entities(inp, out):
  function test_get_report (line 113) | def test_get_report(annots_true, annots_pred):

FILE: github_adventures/neuron/evaluate_noise.py
  function main (line 13) | def main(argv=None):

FILE: github_adventures/neuron/evaluate_shuffling.py
  function main (line 13) | def main(argv=None):

FILE: github_adventures/neuron/evaluate_video.py
  function main (line 12) | def main(argv=None):

FILE: github_adventures/neuron/solutions.py
  class Solution (line 9) | class Solution(abc.ABC):
    method clone (line 19) | def clone(self, obs):
    method get_action (line 23) | def get_action(self, obs):
    method get_n_features (line 27) | def get_n_features(self):
    method reset (line 35) | def reset(self):
    method get_params (line 43) | def get_params(self):
    method set_params (line 60) | def set_params(self, params):
    method get_n_params (line 83) | def get_n_params(self):
  class MLPSolution (line 87) | class MLPSolution(Solution):
    method __init__ (line 107) | def __init__(self, n_features=5, hidden_layer_sizes=(16,)):
    method clone (line 118) | def clone(self):
    method get_action (line 128) | def get_action(self, obs):
    method get_n_features (line 134) | def get_n_features(self):
    method reset (line 137) | def reset(self):
  class PermutationInvariantSolution (line 141) | class PermutationInvariantSolution(Solution):
    method __init__ (line 171) | def __init__(
    method clone (line 194) | def clone(self):
    method get_action (line 204) | def get_action(self, obs):
    method reset (line 212) | def reset(self):
    method get_n_features (line 216) | def get_n_features(self):

FILE: github_adventures/neuron/tasks.py
  class IncompatibleNFeatures (line 8) | class IncompatibleNFeatures(Exception):
  class Task (line 12) | class Task:
    method __init__ (line 51) | def __init__(
    method reset_for_rollout (line 76) | def reset_for_rollout(self):
    method modify_obs (line 87) | def modify_obs(self, obs):
    method rollout (line 108) | def rollout(self, solution):

FILE: github_adventures/neuron/torch_utils.py
  class MLP (line 6) | class MLP(nn.Module):
    method __init__ (line 23) | def __init__(self, n_features, hidden_layer_sizes):
    method forward (line 46) | def forward(self, obs):
  function pos_table (line 64) | def pos_table(n_embeddings, hidden_size):
  class AttentionMatrix (line 96) | class AttentionMatrix(nn.Module):
    method __init__ (line 120) | def __init__(self, hidden_size, proj_dim, scale=True):
    method forward (line 134) | def forward(self, data_q, data_k):
  class AttentionNeuron (line 162) | class AttentionNeuron(nn.Module):
    method __init__ (line 194) | def __init__(
    method forward (line 225) | def forward(self, obs, prev_action):
  class PermutationInvariantNetwork (line 281) | class PermutationInvariantNetwork(nn.Module):
    method __init__ (line 304) | def __init__(
    method forward (line 323) | def forward(self, obs, prev_action):

FILE: github_adventures/neuron/trainer.py
  function save (line 20) | def save(folder, n_iter, solver, solution_inst):
  function get_fitness (line 47) | def get_fitness(
  function main (line 78) | def main(argv=None):

FILE: github_adventures/pondernet/train.py
  function evaluate (line 21) | def evaluate(dataloader, module):
  function plot_distributions (line 102) | def plot_distributions(target, predicted):
  function plot_accuracy (line 142) | def plot_accuracy(accuracy):
  function main (line 173) | def main(argv=None):

FILE: github_adventures/pondernet/utils.py
  class ParityDataset (line 6) | class ParityDataset(Dataset):
    method __init__ (line 22) | def __init__(
    method __len__ (line 39) | def __len__(self):
    method __getitem__ (line 43) | def __getitem__(self, idx):
  class PonderNet (line 60) | class PonderNet(nn.Module):
    method __init__ (line 93) | def __init__(
    method forward (line 106) | def forward(self, x):
  class ReconstructionLoss (line 182) | class ReconstructionLoss(nn.Module):
    method __init__ (line 193) | def __init__(self, loss_func):
    method forward (line 198) | def forward(self, p, y_pred, y_true):
  class RegularizationLoss (line 230) | class RegularizationLoss(nn.Module):
    method __init__ (line 244) | def __init__(self, lambda_p, max_steps=20):
    method forward (line 257) | def forward(self, p):

FILE: github_adventures/product_quantization/convert.py
  function from_faiss (line 14) | def from_faiss(faiss_index: faiss.swigfaiss.IndexPQ) -> CustomIndexPQ:
  function main (line 45) | def main() -> int:

FILE: github_adventures/product_quantization/custom.py
  class CustomIndexPQ (line 16) | class CustomIndexPQ:
    method __init__ (line 36) | def __init__(
    method train (line 66) | def train(self, X: np.ndarray) -> None:
    method encode (line 88) | def encode(self, X: np.ndarray) -> np.ndarray:
    method add (line 111) | def add(self, X: np.ndarray) -> None:
    method compute_asymmetric_distances (line 123) | def compute_asymmetric_distances(self, X: np.ndarray) -> np.ndarray:
    method search (line 164) | def search(self, X: np.ndarray, k: int) -> tuple[np.ndarray, np.ndarray]:

FILE: github_adventures/product_quantization/parse.py
  function get_embeddings (line 15) | def get_embeddings(path: str, maximum: int | None = None) -> tuple[list[...

FILE: github_adventures/product_quantization/run_gradio.py
  function run (line 40) | def run(

FILE: github_adventures/siren/activations.py
  function fh (line 22) | def fh(inst, inp, out, number=0):

FILE: github_adventures/siren/core.py
  function paper_init_ (line 8) | def paper_init_(weight, is_first=False, omega=1):
  class SineLayer (line 33) | class SineLayer(nn.Module):
    method __init__ (line 63) | def __init__(
    method forward (line 81) | def forward(self, x):
  class ImageSiren (line 96) | class ImageSiren(nn.Module):
    method __init__ (line 119) | def __init__(
    method forward (line 163) | def forward(self, x):
  function generate_coordinates (line 180) | def generate_coordinates(n):
  class PixelDataset (line 198) | class PixelDataset(Dataset):
    method __init__ (line 226) | def __init__(self, img):
    method __len__ (line 237) | def __len__(self):
    method __getitem__ (line 241) | def __getitem__(self, idx):
  class GradientUtils (line 258) | class GradientUtils:
    method gradient (line 260) | def gradient(target, coords):
    method divergence (line 281) | def divergence(grad, coords):
    method laplace (line 310) | def laplace(target, coords):

FILE: github_adventures/vision_transformer/custom.py
  class PatchEmbed (line 5) | class PatchEmbed(nn.Module):
    method __init__ (line 31) | def __init__(self, img_size, patch_size, in_chans=3, embed_dim=768):
    method forward (line 45) | def forward(self, x):
  class Attention (line 67) | class Attention(nn.Module):
    method __init__ (line 103) | def __init__(self, dim, n_heads=12, qkv_bias=True, attn_p=0., proj_p=0.):
    method forward (line 115) | def forward(self, x):
  class MLP (line 161) | class MLP(nn.Module):
    method __init__ (line 192) | def __init__(self, in_features, hidden_features, out_features, p=0.):
    method forward (line 199) | def forward(self, x):
  class Block (line 223) | class Block(nn.Module):
    method __init__ (line 255) | def __init__(self, dim, n_heads, mlp_ratio=4.0, qkv_bias=True, p=0., a...
    method forward (line 273) | def forward(self, x):
  class VisionTransformer (line 292) | class VisionTransformer(nn.Module):
    method __init__ (line 349) | def __init__(
    method forward (line 395) | def forward(self, x):

FILE: github_adventures/vision_transformer/verify.py
  function get_n_params (line 7) | def get_n_params(module):
  function assert_tensors_equal (line 10) | def assert_tensors_equal(t1, t2):

FILE: mini_tutorials/bentoml/service.py
  class Request (line 13) | class Request(BaseModel):
  class Response (line 19) | class Response(BaseModel):
  function classify (line 24) | def classify(request: Request) -> Response:

FILE: mini_tutorials/custom_optimizer_in_pytorch/custom.py
  class WeirdDescent (line 5) | class WeirdDescent(Optimizer):
    method __init__ (line 10) | def __init__(self, parameters, lr=1e-3):
    method step (line 14) | def step(self, closure=None):

FILE: mini_tutorials/custom_optimizer_in_pytorch/src.py
  function rosenbrock (line 10) | def rosenbrock(xy):
  function run_optimization (line 27) | def run_optimization(xy_init, optimizer_class, n_iter, **optimizer_kwargs):
  function create_animation (line 67) | def create_animation(paths,

FILE: mini_tutorials/embedding/src.py
  class CharacterDataset (line 12) | class CharacterDataset(Dataset):
    method __init__ (line 41) | def __init__(self, text, window_size=1, vocab_size=50):
    method __len__ (line 56) | def __len__(self):
    method __getitem__ (line 59) | def __getitem__(self, ix):
  class Network (line 68) | class Network(Module):
    method __init__ (line 92) | def __init__(
    method forward (line 117) | def forward(self, x, h=None, c=None):
  function compute_loss (line 149) | def compute_loss(cal, net, dataloader):
  function generate_text (line 160) | def generate_text(n_chars, net, dataset, initial_text="Hello", random_st...

FILE: mini_tutorials/gradient_wrt_input/explain.py
  function func (line 9) | def func(inp, net=None, target=None):
  function compute_integrated_gradients (line 33) | def compute_integrated_gradients(inp, baseline, net, target, n_steps=100):

FILE: mini_tutorials/gradient_wrt_input/fool.py
  function func (line 8) | def func(inp, net=None, target=None):
  function attack (line 33) | def attack(tensor, net, eps=1e-3, n_iter=50):

FILE: mini_tutorials/gradient_wrt_input/utils.py
  function compute_gradient (line 6) | def compute_gradient(func, inp, **kwargs):
  function read_image (line 37) | def read_image(path):
  function to_array (line 64) | def to_array(tensor):
  function scale_grad (line 89) | def scale_grad(grad):

FILE: mini_tutorials/haiku_basics/parameter.py
  function foo (line 8) | def foo(x: jnp.ndarray) -> jnp.ndarray:

FILE: mini_tutorials/haiku_basics/reallife.py
  function foo (line 7) | def foo(x: jnp.ndarray) -> jnp.ndarray:

FILE: mini_tutorials/haiku_basics/state.py
  function foo (line 8) | def foo(x: jnp.ndarray) -> jnp.ndarray:

FILE: mini_tutorials/httpx_rate_limiting/script.py
  function send_request (line 11) | async def send_request(client: httpx.AsyncClient, semaphore: asyncio.Sem...
  function main (line 21) | async def main() -> int:

FILE: mini_tutorials/mocking_neural_networks/app.py
  function get_top_k (line 8) | def get_top_k(sequence, tokenizer, model, k=10):

FILE: mini_tutorials/mocking_neural_networks/test.py
  function test_with_real_objects (line 11) | def test_with_real_objects(k):
  function test_with_mock_objects (line 22) | def test_with_mock_objects(k):

FILE: mini_tutorials/numpy_equality_testing/test.py
  function get_arrays (line 4) | def get_arrays():
  function test___eq__ (line 32) | def test___eq__():
  function test___eq__all (line 38) | def test___eq__all():
  function test_array_equal (line 46) | def test_array_equal():
  function test_allclose (line 56) | def test_allclose():
  function test_testing_array_equal (line 67) | def test_testing_array_equal():
  function test_testing_allclose (line 75) | def test_testing_allclose():

FILE: mini_tutorials/openai_function_calling/example.py
  function get_price (line 17) | def get_price(symbol: str, date: str) -> float:
  function calculate (line 27) | def calculate(a: float, b: float, op: str) -> float:

FILE: mini_tutorials/rag_with_reranking/answer.py
  function generate_prompt (line 9) | def generate_prompt(question: str, contexts: str):

FILE: mini_tutorials/visualizing_activations_with_forward_hooks/src.py
  class Network (line 8) | class Network(Module):
    method __init__ (line 9) | def __init__(self):
    method forward (line 17) | def forward(self, x):
  function activation_hook (line 33) | def activation_hook(inst, inp, out):