code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
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def extract_local(value, rank, world_size, device, dim=1):
"""Extract the local value from the global value."""
value_chunks = value.chunk(2 * world_size, dim=dim)
local_value = torch.cat(
[value_chunks[rank], value_chunks[2 * world_size - rank - 1]], dim=dim
)
return local_value.to(device) | Extract the local value from the global value. | extract_local | python | oumi-ai/oumi | src/oumi/models/layers/ring_attention.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/ring_attention.py | Apache-2.0 |
def prepare_zigzag_ring_attn_inputs(
input_ids, position_ids, target_ids, rank, world_size, device
):
"""Prepare the inputs for zigzag ring attention."""
local_input_ids = extract_local(
input_ids,
rank,
world_size,
device,
)
local_position_ids = extract_local(
... | Prepare the inputs for zigzag ring attention. | prepare_zigzag_ring_attn_inputs | python | oumi-ai/oumi | src/oumi/models/layers/ring_attention.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/ring_attention.py | Apache-2.0 |
def apply_zigzag_ring_attn_monkey_patch_llama():
"""Apply the zigzag ring attention monkey patch to llama."""
if not is_zigzag_ring_flash_attn_available():
raise RuntimeError(
"Ring attention is not available. "
"Install Flash Attention: `pip install flash-attn --no-build-isolati... | Apply the zigzag ring attention monkey patch to llama. | apply_zigzag_ring_attn_monkey_patch_llama | python | oumi-ai/oumi | src/oumi/models/layers/ring_attention.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/ring_attention.py | Apache-2.0 |
def get_default_args(func) -> dict[str, Any]:
"""Get the default arguments of a function."""
spec = inspect.getfullargspec(func)
defaults = spec.defaults if spec.defaults is not None else ()
padded_defaults = (None,) * (len(spec.args) - len(defaults)) + defaults
args: dict[str, Any] = dict(zip(spec.... | Get the default arguments of a function. | get_default_args | python | oumi-ai/oumi | src/oumi/models/layers/zigzag_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/zigzag_utils.py | Apache-2.0 |
def update_out_and_lse(
out: Optional[torch.Tensor],
lse: Optional[torch.Tensor],
block_out: torch.Tensor,
block_lse: torch.Tensor,
slice_=None,
) -> tuple[torch.Tensor, torch.Tensor]:
"""Update the output and log-sum-exp of the attention."""
if out is None:
if slice_ is not None:
... | Update the output and log-sum-exp of the attention. | update_out_and_lse | python | oumi-ai/oumi | src/oumi/models/layers/zigzag_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/zigzag_utils.py | Apache-2.0 |
def flatten_varlen_lse(lse, cu_seqlens):
"""Flatten the log-sum-exp of the attention."""
new_lse = []
for i in range(len(cu_seqlens) - 1):
start, end = cu_seqlens[i], cu_seqlens[i + 1]
new_lse.append(lse[i, :, : end - start])
return torch.cat(new_lse, dim=1) | Flatten the log-sum-exp of the attention. | flatten_varlen_lse | python | oumi-ai/oumi | src/oumi/models/layers/zigzag_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/zigzag_utils.py | Apache-2.0 |
def unflatten_varlen_lse(lse, cu_seqlens, max_seqlen: int):
"""Unflatten the log-sum-exp of the attention."""
num_seq = len(cu_seqlens) - 1
num_head = lse.shape[-2]
new_lse = torch.empty(
(num_seq, max_seqlen, num_head, 1), dtype=torch.float32, device=lse.device
)
for i in range(num_seq)... | Unflatten the log-sum-exp of the attention. | unflatten_varlen_lse | python | oumi-ai/oumi | src/oumi/models/layers/zigzag_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/zigzag_utils.py | Apache-2.0 |
def wait(self):
"""Wait for the operations to complete."""
if self._reqs is None:
raise RuntimeError("wait called before commit")
for req in self._reqs:
req.wait()
self._reqs = None
self._ops = [] | Wait for the operations to complete. | wait | python | oumi-ai/oumi | src/oumi/models/layers/zigzag_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/models/layers/zigzag_utils.py | Apache-2.0 |
def _get_device_flops(device_name: str, dtype: torch.dtype) -> float:
"""Returns peak TFLOPS for the given device name and dtype."""
if device_name not in _DEVICE_SPECS:
raise NotImplementedError(
f"Unknown device name for getting hardware flops: {device_name}"
)
specs = _DEVICE... | Returns peak TFLOPS for the given device name and dtype. | _get_device_flops | python | oumi-ai/oumi | src/oumi/performance/mfu.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/mfu.py | Apache-2.0 |
def _get_model_flops_per_token(
num_params: int,
num_layers: Optional[int] = None,
num_attention_heads: Optional[int] = None,
attention_head_size: Optional[int] = None,
sequence_length: Optional[int] = None,
add_rematerialization: bool = False,
) -> int:
"""Returns the number of FLOPs per to... | Returns the number of FLOPs per token for the given model configuration. | _get_model_flops_per_token | python | oumi-ai/oumi | src/oumi/performance/mfu.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/mfu.py | Apache-2.0 |
def calculate_mfu_from_model_flops_per_second(
device_name: str,
num_devices: int,
dtype: torch.dtype,
model_flops_per_second_on_all_devices: float,
) -> float:
"""Returns the number of MFU for the given model flops per second."""
if num_devices <= 0:
raise ValueError(f"Must have a posit... | Returns the number of MFU for the given model flops per second. | calculate_mfu_from_model_flops_per_second | python | oumi-ai/oumi | src/oumi/performance/mfu.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/mfu.py | Apache-2.0 |
def calculate_mfu(
device_name: str,
num_devices: int,
dtype: torch.dtype,
num_params: int,
num_tokens: int,
delta_time_seconds: float,
num_layers: Optional[int] = None,
num_attention_heads: Optional[int] = None,
attention_head_size: Optional[int] = None,
sequence_length: Optiona... | Returns the number of MFU for the given model configuration. | calculate_mfu | python | oumi-ai/oumi | src/oumi/performance/mfu.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/mfu.py | Apache-2.0 |
def __init__(self, name: str, measurements: Optional[list[float]] = None):
"""Initializes a TimerContext object.
Args:
name: The name of the timer.
measurements: A list to store the timing measurements.
"""
self.name = name
self.measurements = measurement... | Initializes a TimerContext object.
Args:
name: The name of the timer.
measurements: A list to store the timing measurements.
| __init__ | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def __exit__(self, *exc) -> bool:
"""Stops the timer and records the elapsed time."""
if self.start_time is not None:
if self.cuda_synchronize:
torch.cuda.synchronize()
elapsed_time = time.perf_counter() - self.start_time
self.measurements.append(elaps... | Stops the timer and records the elapsed time. | __exit__ | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def __init__(self, name: str, measurements: Optional[list[float]] = None):
"""Initializes a CudaTimerContext object.
Args:
name: The name of the timer.
measurements: A list to store the timing measurements.
"""
self.name = name
self.measurements = measure... | Initializes a CudaTimerContext object.
Args:
name: The name of the timer.
measurements: A list to store the timing measurements.
| __init__ | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def __exit__(self, *exc) -> bool:
"""Stops the CUDA timer and records the elapsed time."""
if not torch.cuda.is_available():
LOGGER.debug("CUDA is not available. Skipping CUDA benchmark.")
return False
assert self.end_event is not None
self.end_event.record()
... | Stops the CUDA timer and records the elapsed time. | __exit__ | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def gpu_memory_logger(user_function: Callable, synchronize: bool = True) -> Callable:
"""Decorator function that logs the GPU memory usage of a given function.
Args:
user_function: The function to be decorated.
synchronize: Flag indicating whether to synchronize
GPU operations before ... | Decorator function that logs the GPU memory usage of a given function.
Args:
user_function: The function to be decorated.
synchronize: Flag indicating whether to synchronize
GPU operations before measuring memory usage. Defaults to True.
Returns:
The decorated function.
| gpu_memory_logger | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def timer(self, name: str) -> TimerContext:
"""Creates a timer with the given name.
Args:
name: The name of the timer.
Returns:
A TimerContext object.
"""
if name not in self.state.measurements:
self.state.measurements[name] = []
retu... | Creates a timer with the given name.
Args:
name: The name of the timer.
Returns:
A TimerContext object.
| timer | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def cuda_timer(self, name: str) -> CudaTimerContext:
"""Creates a CUDA benchmark with the given name.
Args:
name: The name of the benchmark.
Returns:
A CudaTimerContext object.
"""
if name not in self.state.cuda_measurements:
self.state.cuda_... | Creates a CUDA benchmark with the given name.
Args:
name: The name of the benchmark.
Returns:
A CudaTimerContext object.
| cuda_timer | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def log_gpu_memory(self, custom_logger: Optional[Callable] = None) -> None:
"""Logs the GPU memory usage.
Args:
custom_logger: A custom logging function. If None, store in self.gpu_memory.
"""
if not torch.cuda.is_available():
LOGGER.debug("CUDA is not available.... | Logs the GPU memory usage.
Args:
custom_logger: A custom logging function. If None, store in self.gpu_memory.
| log_gpu_memory | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def record_gpu_temperature(self) -> float:
"""Records the current GPU temperature.
Returns:
GPU temperature, in degrees Celsius.
"""
if not torch.cuda.is_available():
LOGGER.debug("CUDA is not available. GPU temperature cannot be logged.")
return 0.0
... | Records the current GPU temperature.
Returns:
GPU temperature, in degrees Celsius.
| record_gpu_temperature | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def get_summary(self) -> dict[str, Any]:
"""Returns a summary of the telemetry statistics.
Returns:
A dictionary containing the summary statistics.
"""
total_time = time.perf_counter() - self.state.start_time
summary = {
_SUMMARY_KEY_HOSTNAME: self.state... | Returns a summary of the telemetry statistics.
Returns:
A dictionary containing the summary statistics.
| get_summary | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def print_summary(self) -> None:
"""Prints a summary of the telemetry statistics."""
summary = self.get_summary()
log_lines: list[str] = [
f"Telemetry Summary ({summary[_SUMMARY_KEY_HOSTNAME]}):",
f"Total time: {summary['total_time']:.2f} seconds",
]
if s... | Prints a summary of the telemetry statistics. | print_summary | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def compute_cross_rank_summaries(
self,
rank_summaries: list[dict[str, Any]],
*,
measurement_names: Union[set[str], dict[str, Any]],
) -> dict[str, Any]:
"""Computes a cross-rank summary from summaries produced by individual ranks.
For example, it can be used to comp... | Computes a cross-rank summary from summaries produced by individual ranks.
For example, it can be used to compute distribution
of `{"gpu_temperature": {"max"}}` over ranks.
Args:
rank_summaries: An array of summaries indexed by rank e.g.,
returned by the `get_summar... | compute_cross_rank_summaries | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def _calculate_timer_stats(
self, measurements: list[float], total_time: Optional[float] = None
) -> dict[str, float]:
"""Same as above but also computes `total` and `percentage`."""
stats: dict[str, float] = self._calculate_basic_stats(measurements)
count = len(measurements)
... | Same as above but also computes `total` and `percentage`. | _calculate_timer_stats | python | oumi-ai/oumi | src/oumi/performance/telemetry.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/telemetry.py | Apache-2.0 |
def _configure_torch_profile_save_dir(
params: ProfilerParams, training_output_dir: Optional[str]
) -> ProfilerParams:
"""Auto-generates ProfilerParams.saved_dir if not specified explicitly."""
if not params.save_dir and training_output_dir:
params.save_dir = str(
pathlib.Path(training_o... | Auto-generates ProfilerParams.saved_dir if not specified explicitly. | _configure_torch_profile_save_dir | python | oumi-ai/oumi | src/oumi/performance/torch_profiler_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/torch_profiler_utils.py | Apache-2.0 |
def torch_profile(
params: ProfilerParams,
*,
training_output_dir: Optional[str],
record_function_name: str = "oumi.train",
):
"""Creates PyTorch Profiler context manager.
Args:
params: Profiler config.
training_output_dir: If `ProfilerParams.save_dir` is not specified, then
... | Creates PyTorch Profiler context manager.
Args:
params: Profiler config.
training_output_dir: If `ProfilerParams.save_dir` is not specified, then
a "profiler" sub-directory will be created under `training_output_dir`,
and used to save profiler traces.
record_function... | torch_profile | python | oumi-ai/oumi | src/oumi/performance/torch_profiler_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/performance/torch_profiler_utils.py | Apache-2.0 |
def batch(dataset: list[T], batch_size: int) -> list[list[T]]:
"""Batches the provided dataset.
Args:
dataset: The dataset to batch, which is a flat list of items.
batch_size: The desired size of each batch.
Returns:
A list of batches. Each batch is a list of `batch_size` items, as... | Batches the provided dataset.
Args:
dataset: The dataset to batch, which is a flat list of items.
batch_size: The desired size of each batch.
Returns:
A list of batches. Each batch is a list of `batch_size` items, assuming that
the dataset's size is a multiple of `batch_size`. ... | batch | python | oumi-ai/oumi | src/oumi/utils/batching.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/batching.py | Apache-2.0 |
def load_image_bytes_to_content_item(
item: ContentItem, mode: str = DEFAULT_IMAGE_MODE
) -> ContentItem:
"""Ensures that message content item contains inline image bytes if it's an image.
Loads image content if image type is `IMAGE_URL` or `IMAGE_PATH`.
Otherwise returns the input content item w/o any... | Ensures that message content item contains inline image bytes if it's an image.
Loads image content if image type is `IMAGE_URL` or `IMAGE_PATH`.
Otherwise returns the input content item w/o any changes.
Args:
item: An input message content item.
mode: The requested image mode e.g., "RGB",... | load_image_bytes_to_content_item | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def load_pil_image_from_content_item(
image_item: ContentItem, mode: str = DEFAULT_IMAGE_MODE
) -> PIL.Image.Image:
"""Loads a PIL image from a message content item.
Args:
image_item: A content item representing an image.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
... | Loads a PIL image from a message content item.
Args:
image_item: A content item representing an image.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow.readthedocs.io/en/stable/handbook/conc... | load_pil_image_from_content_item | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def base64encode_content_item_image_bytes(
item: ContentItem, *, add_mime_prefix: bool = True
) -> str:
"""Creates base-64 encoded image bytes as ASCII string value.
Args:
item: An input message content item of image type
(one of `IMAGE_BINARY`, `IMAGE_PATH, `IMAGE_URL`)
wit... | Creates base-64 encoded image bytes as ASCII string value.
Args:
item: An input message content item of image type
(one of `IMAGE_BINARY`, `IMAGE_PATH, `IMAGE_URL`)
with the pre-populated `binary` field.
add_mime_prefix: Whether to add MIME prefix `data:image/png;base64,`
... | base64encode_content_item_image_bytes | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def convert_message_content_item_to_json_dict(
item: ContentItem,
) -> dict[str, Any]:
"""Returns the content for a message content item.
Args:
item: The message content item to get the content for.
Returns:
Dict[str, Any]: The content for the message.
"""
if item.type == Type.... | Returns the content for a message content item.
Args:
item: The message content item to get the content for.
Returns:
Dict[str, Any]: The content for the message.
| convert_message_content_item_to_json_dict | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def convert_content_items_to_json_list(
content_items: list[ContentItem],
) -> list[dict[str, Any]]:
"""Converts content items to a list of JSON dicts.
Args:
content_items: A list of content items.
Returns:
list[Dict[str, Any]]: The list of all content items encoded as JSON dicts.
... | Converts content items to a list of JSON dicts.
Args:
content_items: A list of content items.
Returns:
list[Dict[str, Any]]: The list of all content items encoded as JSON dicts.
| convert_content_items_to_json_list | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def convert_message_to_json_content_list(
message: Message,
) -> list[dict[str, Any]]:
"""Returns the message content as a list of its content items encoded as JSON dicts.
Args:
message: The message to get the content for.
Returns:
list[Dict[str, Any]]: The content for the message for ... | Returns the message content as a list of its content items encoded as JSON dicts.
Args:
message: The message to get the content for.
Returns:
list[Dict[str, Any]]: The content for the message for all content items.
| convert_message_to_json_content_list | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def convert_message_to_json_content(
message: Message,
) -> Union[str, list[dict[str, Any]]]:
"""Returns the message content.
Args:
message: The message to get the content for.
Returns:
The content for the message returned either as a single string,
or as a list of content item... | Returns the message content.
Args:
message: The message to get the content for.
Returns:
The content for the message returned either as a single string,
or as a list of content items.
| convert_message_to_json_content | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def create_list_of_message_json_dicts(
messages: list[Message],
*,
group_adjacent_same_role_turns: bool,
) -> list[dict[str, Any]]:
"""Returns a list of JSON dictionaries representing messages.
Loads image bytes and encodes them as base64.
Args:
messages: The input messages.
gr... | Returns a list of JSON dictionaries representing messages.
Loads image bytes and encodes them as base64.
Args:
messages: The input messages.
group_adjacent_same_role_turns: Whether to pack adjacent messages
from the same role into a single element in output list.
Returns:
... | create_list_of_message_json_dicts | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def truncate_text_in_content_items(
messages: list[Message],
tokenizer: BaseTokenizer,
*,
max_tokens: int,
truncation_side: str = "right",
) -> list[Message]:
"""Truncates text contents in Messages to `max_length` total tokens.
Note that we have to truncate plain texts *before* we apply cha... | Truncates text contents in Messages to `max_length` total tokens.
Note that we have to truncate plain texts *before* we apply chat template
as the final processed prompt is generally unsafe to truncate at arbitrary
offset: it may break invariants (e.g., prompt contains `N` images tokens)
leading to run... | truncate_text_in_content_items | python | oumi-ai/oumi | src/oumi/utils/conversation_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/conversation_utils.py | Apache-2.0 |
def log_example_for_debugging(
raw_example: Any,
formatted_example: str,
tokenized_example: list[tuple[int, str]],
model_input: dict[str, Any],
) -> None:
"""Logs an example of the data in each step for debugging purposes.
Args:
raw_example: The raw example from the dataset.
for... | Logs an example of the data in each step for debugging purposes.
Args:
raw_example: The raw example from the dataset.
formatted_example: The formatted example after processing.
tokenized_example: The tokenized example after tokenization.
model_input: The final model input after coll... | log_example_for_debugging | python | oumi-ai/oumi | src/oumi/utils/debug_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/debug_utils.py | Apache-2.0 |
def _initialize_pynvml() -> bool:
"""Attempts to initialize pynvml library. Returns True on success."""
global pynvml
if pynvml is None:
return False
try:
pynvml.nvmlInit()
except Exception:
logger.error(
"Failed to initialize pynvml library. All pynvml calls wil... | Attempts to initialize pynvml library. Returns True on success. | _initialize_pynvml | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def _initialize_pynvml_and_get_pynvml_device_count() -> Optional[int]:
"""Attempts to initialize pynvml library.
Returns device count on success, or None otherwise.
"""
global pynvml
# The call to `pynvml is None` is technically redundant but exists here
# to make pyright happy.
if pynvml i... | Attempts to initialize pynvml library.
Returns device count on success, or None otherwise.
| _initialize_pynvml_and_get_pynvml_device_count | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def get_nvidia_gpu_runtime_info(
device_index: int = 0,
) -> Optional[NVidiaGpuRuntimeInfo]:
"""Returns runtime stats for Nvidia GPU."""
return _get_nvidia_gpu_runtime_info_impl(
device_index=device_index,
memory=True,
temperature=True,
fan_speed=True,
power_usage=Tru... | Returns runtime stats for Nvidia GPU. | get_nvidia_gpu_runtime_info | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def log_nvidia_gpu_runtime_info(device_index: int = 0, log_prefix: str = "") -> None:
"""Prints the current NVIDIA GPU runtime info."""
info = get_nvidia_gpu_runtime_info(device_index)
logger.info(f"{log_prefix.rstrip()} GPU runtime info: {pformat(info)}.") | Prints the current NVIDIA GPU runtime info. | log_nvidia_gpu_runtime_info | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def get_nvidia_gpu_memory_utilization(device_index: int = 0) -> float:
"""Returns amount of memory being used on an Nvidia GPU in MiB."""
info: Optional[NVidiaGpuRuntimeInfo] = _get_nvidia_gpu_runtime_info_impl(
device_index=device_index, memory=True
)
return (
info.used_memory_mb
... | Returns amount of memory being used on an Nvidia GPU in MiB. | get_nvidia_gpu_memory_utilization | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def log_nvidia_gpu_memory_utilization(
device_index: int = 0, log_prefix: str = ""
) -> None:
"""Prints amount of memory being used on an Nvidia GPU."""
memory_mib = get_nvidia_gpu_memory_utilization(device_index)
logger.info(f"{log_prefix.rstrip()} GPU memory occupied: {memory_mib} MiB.") | Prints amount of memory being used on an Nvidia GPU. | log_nvidia_gpu_memory_utilization | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def get_nvidia_gpu_temperature(device_index: int = 0) -> int:
"""Returns the current temperature readings for the device, in degrees C."""
info: Optional[NVidiaGpuRuntimeInfo] = _get_nvidia_gpu_runtime_info_impl(
device_index=device_index,
temperature=True,
)
return (
info.temper... | Returns the current temperature readings for the device, in degrees C. | get_nvidia_gpu_temperature | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def log_nvidia_gpu_temperature(device_index: int = 0, log_prefix: str = "") -> None:
"""Prints the current temperature readings for the device, in degrees C."""
temperature = get_nvidia_gpu_temperature(device_index)
logger.info(f"{log_prefix.rstrip()} GPU temperature: {temperature} C.") | Prints the current temperature readings for the device, in degrees C. | log_nvidia_gpu_temperature | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def get_nvidia_gpu_fan_speeds(device_index: int = 0) -> Sequence[int]:
"""Returns the current fan speeds for NVIDIA GPU device."""
info: Optional[NVidiaGpuRuntimeInfo] = _get_nvidia_gpu_runtime_info_impl(
device_index=device_index, fan_speed=True
)
return (
info.fan_speeds
if (in... | Returns the current fan speeds for NVIDIA GPU device. | get_nvidia_gpu_fan_speeds | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def log_nvidia_gpu_fan_speeds(device_index: int = 0, log_prefix: str = "") -> None:
"""Prints the current NVIDIA GPU fan speeds."""
fan_speeds = get_nvidia_gpu_fan_speeds(device_index)
logger.info(f"{log_prefix.rstrip()} GPU fan speeds: {fan_speeds}.") | Prints the current NVIDIA GPU fan speeds. | log_nvidia_gpu_fan_speeds | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def get_nvidia_gpu_power_usage(device_index: int = 0) -> float:
"""Returns the current power usage for NVIDIA GPU device."""
info: Optional[NVidiaGpuRuntimeInfo] = _get_nvidia_gpu_runtime_info_impl(
device_index=device_index, power_usage=True
)
return (
info.power_usage_watts
if ... | Returns the current power usage for NVIDIA GPU device. | get_nvidia_gpu_power_usage | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def log_nvidia_gpu_power_usage(device_index: int = 0, log_prefix: str = "") -> None:
"""Prints the current NVIDIA GPU power usage."""
power_usage = get_nvidia_gpu_power_usage(device_index)
logger.info(f"{log_prefix.rstrip()} GPU power usage: {power_usage:.2f}W.") | Prints the current NVIDIA GPU power usage. | log_nvidia_gpu_power_usage | python | oumi-ai/oumi | src/oumi/utils/device_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/device_utils.py | Apache-2.0 |
def is_using_accelerate() -> bool:
"""Returns whether the current job was launched with the Accelerate launcher.
We do this by checking if the `ACCELERATE_DYNAMO_*` environment variables are set.
These variables should always be set by Accelerate. We check for all of them in case
Accelerate changes the... | Returns whether the current job was launched with the Accelerate launcher.
We do this by checking if the `ACCELERATE_DYNAMO_*` environment variables are set.
These variables should always be set by Accelerate. We check for all of them in case
Accelerate changes the environment variables in the future.
| is_using_accelerate | python | oumi-ai/oumi | src/oumi/utils/distributed_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/distributed_utils.py | Apache-2.0 |
def get_git_revision_hash() -> Optional[str]:
"""Get the current git revision hash.
Returns:
Optional[str]: The current git revision hash, or None if it cannot be retrieved.
"""
try:
return subprocess.check_output(
["git", "rev-parse", "HEAD"],
cwd=Path(__file__)... | Get the current git revision hash.
Returns:
Optional[str]: The current git revision hash, or None if it cannot be retrieved.
| get_git_revision_hash | python | oumi-ai/oumi | src/oumi/utils/git_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/git_utils.py | Apache-2.0 |
def get_git_tag() -> Optional[str]:
"""Get the current git tag.
Returns:
Optional[str]: The current git tag, or None if it cannot be retrieved.
"""
try:
return subprocess.check_output(
["git", "describe", "--tags", "--abbrev=0", "--exact-match"],
cwd=Path(__file_... | Get the current git tag.
Returns:
Optional[str]: The current git tag, or None if it cannot be retrieved.
| get_git_tag | python | oumi-ai/oumi | src/oumi/utils/git_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/git_utils.py | Apache-2.0 |
def get_git_root_dir() -> Optional[Path]:
"""Get the root directory of the current git repository.
Returns:
Optional[str]: The root directory of the current git repository, or None if it
cannot be retrieved.
"""
try:
dir_path = Path(
subprocess.check_output(
... | Get the root directory of the current git repository.
Returns:
Optional[str]: The root directory of the current git repository, or None if it
cannot be retrieved.
| get_git_root_dir | python | oumi-ai/oumi | src/oumi/utils/git_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/git_utils.py | Apache-2.0 |
def extract_prompt_images_completion_from_single_turn_conversation(
example: dict,
) -> tuple[str, list, str]:
"""Finds prompt, completion, and optional images in a single-turn conversation.
Args:
example: A dictionary containing the conversation JSON.
Returns:
A tuple containing the p... | Finds prompt, completion, and optional images in a single-turn conversation.
Args:
example: A dictionary containing the conversation JSON.
Returns:
A tuple containing the prompt, images, and completion.
The list of images is empty for text-only conversations.
| extract_prompt_images_completion_from_single_turn_conversation | python | oumi-ai/oumi | src/oumi/utils/grpo_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/grpo_utils.py | Apache-2.0 |
def try_prepare_trl_grpo_example(
example: dict,
) -> dict:
"""Prepares an example for GRPO_TRL processing.
This function checks if the input example is one of known special cases
e.g., SFT example, and transforms it into a GRPO compatible format.
Otherwise, it returns the original example.
Ar... | Prepares an example for GRPO_TRL processing.
This function checks if the input example is one of known special cases
e.g., SFT example, and transforms it into a GRPO compatible format.
Otherwise, it returns the original example.
Args:
example (dict): The input example.
Returns:
GR... | try_prepare_trl_grpo_example | python | oumi-ai/oumi | src/oumi/utils/grpo_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/grpo_utils.py | Apache-2.0 |
def is_cached_to_disk_hf_dataset(dataset_folder: Union[str, Path]) -> bool:
"""Detects whether a dataset was saved using `dataset.save_to_disk()`.
Such datasets should be loaded using `datasets.Dataset.load_from_disk()`
Returns:
Whether the dataset was saved using `dataset.save_to_disk()` method.
... | Detects whether a dataset was saved using `dataset.save_to_disk()`.
Such datasets should be loaded using `datasets.Dataset.load_from_disk()`
Returns:
Whether the dataset was saved using `dataset.save_to_disk()` method.
| is_cached_to_disk_hf_dataset | python | oumi-ai/oumi | src/oumi/utils/hf_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/hf_utils.py | Apache-2.0 |
def find_hf_token() -> Optional[str]:
"""Attempts to find HuggingFace access token.
Returns:
A valid HF access token, or `None` if not found.
"""
hf_token = os.environ.get("HF_TOKEN", None)
if not hf_token:
_DEFAULT_HF_HOME_PATH = "~/.cache/huggingface"
file_must_exist = Fa... | Attempts to find HuggingFace access token.
Returns:
A valid HF access token, or `None` if not found.
| find_hf_token | python | oumi-ai/oumi | src/oumi/utils/hf_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/hf_utils.py | Apache-2.0 |
def get_hf_chat_template(
tokenizer_name: str, *, trust_remote_code: bool = False
) -> Optional[str]:
"""Returns chat template provided by HF for `tokenizer_name`."""
if not tokenizer_name or is_custom_model(tokenizer_name):
return None
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | Returns chat template provided by HF for `tokenizer_name`. | get_hf_chat_template | python | oumi-ai/oumi | src/oumi/utils/hf_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/hf_utils.py | Apache-2.0 |
async def get_failure_reason_from_response(
response: aiohttp.ClientResponse,
) -> str:
"""Return a string describing the error from the provided response."""
try:
response_json = await response.json()
if isinstance(response_json, list):
response_json = response_json[0]
e... | Return a string describing the error from the provided response. | get_failure_reason_from_response | python | oumi-ai/oumi | src/oumi/utils/http.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/http.py | Apache-2.0 |
def create_png_bytes_from_image(pil_image: PIL.Image.Image) -> bytes:
"""Encodes PIL image into PNG format, and returns PNG image bytes.
Args:
pil_image: An input image.
Returns:
bytes: PNG bytes representation of the image.
"""
try:
output = io.BytesIO()
pil_image.... | Encodes PIL image into PNG format, and returns PNG image bytes.
Args:
pil_image: An input image.
Returns:
bytes: PNG bytes representation of the image.
| create_png_bytes_from_image | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def convert_pil_image_mode(
image: PIL.Image.Image, *, mode: Optional[str]
) -> PIL.Image.Image:
"""Converts a PIL image to the requested mode (if it's not in that mode already) .
Args:
image: An input image.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit ... | Converts a PIL image to the requested mode (if it's not in that mode already) .
Args:
image: An input image.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow.readthedocs.io/en/stable/handboo... | convert_pil_image_mode | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pil_image_from_path(
input_image_filepath: Union[str, Path], mode: str = DEFAULT_IMAGE_MODE
) -> PIL.Image.Image:
"""Loads an image from a path.
Args:
input_image_filepath: A file path of an image.
The image can be in any format supported by PIL.
mode: The requested ima... | Loads an image from a path.
Args:
input_image_filepath: A file path of an image.
The image can be in any format supported by PIL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow... | load_pil_image_from_path | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pil_image_from_url(
input_image_url: str, mode: str = DEFAULT_IMAGE_MODE
) -> PIL.Image.Image:
"""Loads a PIL image from a URL.
Args:
input_image_url: An image URL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
... | Loads a PIL image from a URL.
Args:
input_image_url: An image URL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow.readthedocs.io/en/stable/handbook/concepts.html#modes
Returns:
... | load_pil_image_from_url | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pil_image_from_bytes(
image_bytes: Optional[bytes], mode: str = DEFAULT_IMAGE_MODE
) -> PIL.Image.Image:
"""Loads an image from raw image bytes.
Args:
image_bytes: A input image bytes. Can be in any image format supported by PIL.
mode: The requested image mode e.g., "RGB", "HSV", "... | Loads an image from raw image bytes.
Args:
image_bytes: A input image bytes. Can be in any image format supported by PIL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow.readthedocs.io/en/s... | load_pil_image_from_bytes | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pdf_pages_from_path(
input_pdf_filepath: Union[str, Path],
*,
dpi: int = _DEFAULT_PDF_DPI,
mode: str = DEFAULT_IMAGE_MODE,
) -> list[PIL.Image.Image]:
"""Loads PDF pages as PIL images from a path.
Args:
input_pdf_filepath: A file path of an PDF document.
dpi: Resolution... | Loads PDF pages as PIL images from a path.
Args:
input_pdf_filepath: A file path of an PDF document.
dpi: Resolution to use for PDF page images (dots per inch).
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For ... | load_pdf_pages_from_path | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pdf_pages_from_bytes(
pdf_bytes: Optional[bytes],
*,
dpi: int = _DEFAULT_PDF_DPI,
mode: str = DEFAULT_IMAGE_MODE,
) -> list[PIL.Image.Image]:
"""Loads PDF pages as PIL images from raw PDF file bytes.
Args:
pdf_bytes: PDF file content.
dpi: Resolution to use for PDF page... | Loads PDF pages as PIL images from raw PDF file bytes.
Args:
pdf_bytes: PDF file content.
dpi: Resolution to use for PDF page images (dots per inch).
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, se... | load_pdf_pages_from_bytes | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_pdf_pages_from_url(
pdf_url: str, *, dpi: int = _DEFAULT_PDF_DPI, mode: str = DEFAULT_IMAGE_MODE
) -> list[PIL.Image.Image]:
"""Loads PDF pages as PIL images from from PDF URL.
Args:
pdf_url: A PDF URL.
dpi: Resolution to use for PDF page images (dots per inch).
mode: The r... | Loads PDF pages as PIL images from from PDF URL.
Args:
pdf_url: A PDF URL.
dpi: Resolution to use for PDF page images (dots per inch).
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillo... | load_pdf_pages_from_url | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def create_png_bytes_from_image_bytes(
image_bytes: Optional[bytes], mode: str = DEFAULT_IMAGE_MODE
) -> bytes:
"""Loads an image from raw image bytes, and converts to PNG image bytes.
Args:
image_bytes: A input image bytes. Can be in any image format supported by PIL.
mode: The requested i... | Loads an image from raw image bytes, and converts to PNG image bytes.
Args:
image_bytes: A input image bytes. Can be in any image format supported by PIL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see h... | create_png_bytes_from_image_bytes | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_image_png_bytes_from_path(
input_image_filepath: Union[str, Path], mode: str = DEFAULT_IMAGE_MODE
) -> bytes:
"""Loads an image from a path, converts it to PNG, and returns image bytes.
Args:
input_image_filepath: A file path of an image.
The image can be in any format supporte... | Loads an image from a path, converts it to PNG, and returns image bytes.
Args:
input_image_filepath: A file path of an image.
The image can be in any format supported by PIL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette)... | load_image_png_bytes_from_path | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_image_png_bytes_from_url(
input_image_url: str, mode: str = DEFAULT_IMAGE_MODE
) -> bytes:
"""Loads an image from a URL, converts it to PNG, and returns image bytes.
Args:
input_image_url: An image URL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-b... | Loads an image from a URL, converts it to PNG, and returns image bytes.
Args:
input_image_url: An image URL.
mode: The requested image mode e.g., "RGB", "HSV", "RGBA",
"P" (8-bit pixels, using a color palette).
For details, see https://pillow.readthedocs.io/en/stable/handboo... | load_image_png_bytes_from_url | python | oumi-ai/oumi | src/oumi/utils/image_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/image_utils.py | Apache-2.0 |
def load_json(filename: Union[str, Path]) -> Any:
"""Load JSON data from a file.
Args:
filename: Path to the JSON file.
Returns:
dict: Parsed JSON data.
Raises:
FileNotFoundError: If the file doesn't exist.
json.JSONDecodeError: If the file contains invalid JSON.
"... | Load JSON data from a file.
Args:
filename: Path to the JSON file.
Returns:
dict: Parsed JSON data.
Raises:
FileNotFoundError: If the file doesn't exist.
json.JSONDecodeError: If the file contains invalid JSON.
| load_json | python | oumi-ai/oumi | src/oumi/utils/io_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/io_utils.py | Apache-2.0 |
def save_json(
data: dict[str, Any], filename: Union[str, Path], indent: int = 2
) -> None:
"""Save data as a formatted JSON file.
Args:
data: The data to be saved as JSON.
filename: Path where the JSON file will be saved.
indent: Number of spaces for indentation. Defaults to 2.
... | Save data as a formatted JSON file.
Args:
data: The data to be saved as JSON.
filename: Path where the JSON file will be saved.
indent: Number of spaces for indentation. Defaults to 2.
Raises:
TypeError: If the data is not JSON serializable.
| save_json | python | oumi-ai/oumi | src/oumi/utils/io_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/io_utils.py | Apache-2.0 |
def load_file(filename: Union[str, Path], encoding: str = "utf-8") -> str:
"""Load a file as a string.
Args:
filename: Path to the file.
encoding: Encoding to use when reading the file. Defaults to "utf-8".
Returns:
str: The content of the file.
Raises:
FileNotFoundErr... | Load a file as a string.
Args:
filename: Path to the file.
encoding: Encoding to use when reading the file. Defaults to "utf-8".
Returns:
str: The content of the file.
Raises:
FileNotFoundError: If the file doesn't exist.
| load_file | python | oumi-ai/oumi | src/oumi/utils/io_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/io_utils.py | Apache-2.0 |
def load_jsonlines(filename: Union[str, Path]) -> list[dict[str, Any]]:
"""Load a jsonlines file.
Args:
filename: Path to the jsonlines file.
Returns:
List[Dict[str, Any]]: A list of dictionaries, each representing a
JSON object from the file.
Raises:
FileNotFoundE... | Load a jsonlines file.
Args:
filename: Path to the jsonlines file.
Returns:
List[Dict[str, Any]]: A list of dictionaries, each representing a
JSON object from the file.
Raises:
FileNotFoundError: If the file doesn't exist.
jsonlines.InvalidLineError: If the fil... | load_jsonlines | python | oumi-ai/oumi | src/oumi/utils/io_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/io_utils.py | Apache-2.0 |
def save_jsonlines(filename: Union[str, Path], data: list[dict[str, Any]]) -> None:
"""Save a list of dictionaries to a jsonlines file.
Args:
filename: Path to the jsonlines file to be created or overwritten.
data: A list of dictionaries to be saved as JSON objects.
Raises:
IOError... | Save a list of dictionaries to a jsonlines file.
Args:
filename: Path to the jsonlines file to be created or overwritten.
data: A list of dictionaries to be saved as JSON objects.
Raises:
IOError: If there's an error writing to the file.
| save_jsonlines | python | oumi-ai/oumi | src/oumi/utils/io_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/io_utils.py | Apache-2.0 |
def get_logger(
name: str,
level: str = "info",
log_dir: Optional[Union[str, Path]] = None,
) -> logging.Logger:
"""Gets a logger instance with the specified name and log level.
Args:
name : The name of the logger.
level (optional): The log level to set for the logger. Defaults to "... | Gets a logger instance with the specified name and log level.
Args:
name : The name of the logger.
level (optional): The log level to set for the logger. Defaults to "info".
log_dir (optional): Directory to store log files. Defaults to None.
Returns:
logging.Logger: The logger ... | get_logger | python | oumi-ai/oumi | src/oumi/utils/logging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/logging.py | Apache-2.0 |
def _detect_rank() -> int:
"""Detects rank.
Reading the rank from the environment variables instead of
get_device_rank_info to avoid circular imports.
"""
for var_name in (
"RANK",
"SKYPILOT_NODE_RANK", # SkyPilot
"PMI_RANK", # HPC
):
rank = os.environ.get(var_... | Detects rank.
Reading the rank from the environment variables instead of
get_device_rank_info to avoid circular imports.
| _detect_rank | python | oumi-ai/oumi | src/oumi/utils/logging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/logging.py | Apache-2.0 |
def configure_logger(
name: str,
level: str = "info",
log_dir: Optional[Union[str, Path]] = None,
) -> None:
"""Configures a logger with the specified name and log level."""
logger = logging.getLogger(name)
# Remove any existing handlers
logger.handlers = []
# Configure the logger
... | Configures a logger with the specified name and log level. | configure_logger | python | oumi-ai/oumi | src/oumi/utils/logging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/logging.py | Apache-2.0 |
def update_logger_level(name: str, level: str = "info") -> None:
"""Updates the log level of the logger.
Args:
name (str): The logger instance to update.
level (str, optional): The log level to set for the logger. Defaults to "info".
"""
logger = get_logger(name, level=level)
logger... | Updates the log level of the logger.
Args:
name (str): The logger instance to update.
level (str, optional): The log level to set for the logger. Defaults to "info".
| update_logger_level | python | oumi-ai/oumi | src/oumi/utils/logging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/logging.py | Apache-2.0 |
def configure_dependency_warnings(level: Union[str, int] = "info") -> None:
"""Ignores non-critical warnings from dependencies, unless in debug mode.
Args:
level (str, optional): The log level to set for the logger. Defaults to "info".
"""
level_value = logging.DEBUG
if isinstance(level, st... | Ignores non-critical warnings from dependencies, unless in debug mode.
Args:
level (str, optional): The log level to set for the logger. Defaults to "info".
| configure_dependency_warnings | python | oumi-ai/oumi | src/oumi/utils/logging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/logging.py | Apache-2.0 |
def is_power_of_two(n: int) -> bool:
"""Check if a number is a power of two.
Args:
n (int): The number to check.
Returns:
bool: True if n is a power of two, False otherwise.
"""
n = abs(n)
return (n != 0) and (n & (n - 1) == 0) | Check if a number is a power of two.
Args:
n (int): The number to check.
Returns:
bool: True if n is a power of two, False otherwise.
| is_power_of_two | python | oumi-ai/oumi | src/oumi/utils/math_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/math_utils.py | Apache-2.0 |
def get_local_filepath_for_gguf(
repo_id: str, filename: str, cache_dir=HUGGINGFACE_CACHE
) -> str:
"""Return a local path for the provided GGUF file, downloading it if necessary.
Args:
repo_id: HuggingFace Hub repo ID (e.g., `bartowski/Llama-3.2-3B-Instruct-GGUF`)
filename: HuggingFace Hub... | Return a local path for the provided GGUF file, downloading it if necessary.
Args:
repo_id: HuggingFace Hub repo ID (e.g., `bartowski/Llama-3.2-3B-Instruct-GGUF`)
filename: HuggingFace Hub filename (e.g., `Llama-3.2-3B-Instruct-Q8_0.gguf`)
cache_dir: Local path to cached models. Defaults to... | get_local_filepath_for_gguf | python | oumi-ai/oumi | src/oumi/utils/model_caching.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/model_caching.py | Apache-2.0 |
def _version_bounds_str(min_package_version, max_package_version):
"""Returns a string representation of the version bounds."""
if min_package_version is not None and max_package_version is not None:
return f"{min_package_version} <= version <= {max_package_version}"
elif min_package_version is not ... | Returns a string representation of the version bounds. | _version_bounds_str | python | oumi-ai/oumi | src/oumi/utils/packaging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/packaging.py | Apache-2.0 |
def _package_error_message(
package_name: str,
actual_package_version: Union[version.Version, None],
min_package_version: Optional[version.Version] = None,
max_package_version: Optional[version.Version] = None,
) -> Union[str, None]:
"""Checks if a package is installed and if its version is compatib... | Checks if a package is installed and if its version is compatible.
This function checks if the package with name `package_name` is installed and if the
installed version (`actual_package_version`) is compatible with the required
version range. The installed version is considered compatible if it is
bot... | _package_error_message | python | oumi-ai/oumi | src/oumi/utils/packaging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/packaging.py | Apache-2.0 |
def _package_prerequisites_error_messages(
package_prerequisites: list[PackagePrerequisites],
) -> list[str]:
"""Checks if a list of package prerequisites are satisfied.
This function checks if a list of package prerequisites are satisfied and returns an
error message for each package that is not insta... | Checks if a list of package prerequisites are satisfied.
This function checks if a list of package prerequisites are satisfied and returns an
error message for each package that is not installed or has an incompatible version.
If the function returns an empty list, all prerequisites are satisfied.
| _package_prerequisites_error_messages | python | oumi-ai/oumi | src/oumi/utils/packaging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/packaging.py | Apache-2.0 |
def check_package_prerequisites(
package_prerequisites: list[PackagePrerequisites],
runtime_error_prefix: str = RUNTIME_ERROR_PREFIX,
runtime_error_suffix: str = RUNTIME_ERROR_SUFFIX,
) -> None:
"""Checks if the package prerequisites are satisfied and raises an error if not."""
if error_messages := ... | Checks if the package prerequisites are satisfied and raises an error if not. | check_package_prerequisites | python | oumi-ai/oumi | src/oumi/utils/packaging.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/packaging.py | Apache-2.0 |
def get_lora_rank(adapter_dir: Union[str, Path]) -> int:
"""Gets the LoRA rank for a saved adapter model.
Example config:
https://github.com/huggingface/peft/blob/b5db9c935021a54fb5d1a479457ce63ad94e2fe5/docs/source/developer_guides/checkpoint.md?plain=1#L182
Args:
adapter_dir: The directory c... | Gets the LoRA rank for a saved adapter model.
Example config:
https://github.com/huggingface/peft/blob/b5db9c935021a54fb5d1a479457ce63ad94e2fe5/docs/source/developer_guides/checkpoint.md?plain=1#L182
Args:
adapter_dir: The directory containing the adapter model.
Returns:
int: The LoRA... | get_lora_rank | python | oumi-ai/oumi | src/oumi/utils/peft_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/peft_utils.py | Apache-2.0 |
def load_infer_prob(input_filepath: str) -> list[list[list[float]]]:
"""Retrieve batched probabilities from a parquet file."""
probs_count_in_first_batch = None
def to_list(probs):
"""Ensure number of probabilities is the same for all entries."""
probs_list = list(probs)
nonlocal pr... | Retrieve batched probabilities from a parquet file. | load_infer_prob | python | oumi-ai/oumi | src/oumi/utils/saver.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/saver.py | Apache-2.0 |
def to_list(probs):
"""Ensure number of probabilities is the same for all entries."""
probs_list = list(probs)
nonlocal probs_count_in_first_batch
probs_count_in_first_batch = probs_count_in_first_batch or len(probs_list)
if probs_count_in_first_batch != len(probs_list):
... | Ensure number of probabilities is the same for all entries. | to_list | python | oumi-ai/oumi | src/oumi/utils/saver.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/saver.py | Apache-2.0 |
def save_infer_prob_csv(output_filepath: str, probabilities: list[list[list[float]]]):
"""Save batched probabilities into a csv file."""
with open(output_filepath, "w") as write_obj:
csv_writer = csv.writer(write_obj)
csv_writer.writerows(probabilities) | Save batched probabilities into a csv file. | save_infer_prob_csv | python | oumi-ai/oumi | src/oumi/utils/saver.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/saver.py | Apache-2.0 |
def load_infer_prob_csv(input_filepath: str) -> list[list[list[float]]]:
"""Retrieve batched probabilities from a csv file."""
probs_count_in_first_batch = None
try:
with open(input_filepath) as read_obj:
csv_reader = csv.reader(read_obj)
probabilities = []
for b... | Retrieve batched probabilities from a csv file. | load_infer_prob_csv | python | oumi-ai/oumi | src/oumi/utils/saver.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/saver.py | Apache-2.0 |
def str_to_float_list(input: str) -> list[float]:
"""Convert an `str` representing a list of `floats` to an actual list of `floats`.
Example: input: `[1.1, 2.2, 3.3]` => output: [1.1, 2.2, 3.3]
"""
# 1) Get rid of '[' and ']'.
if (input[0] != "[") or (input[-1] != "]"):
raise ValueError(
... | Convert an `str` representing a list of `floats` to an actual list of `floats`.
Example: input: `[1.1, 2.2, 3.3]` => output: [1.1, 2.2, 3.3]
| str_to_float_list | python | oumi-ai/oumi | src/oumi/utils/saver.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/saver.py | Apache-2.0 |
def default(self, obj):
"""Extending python's JSON Encoder to serialize torch dtype."""
if obj is None:
return ""
# JSON does NOT natively support any torch types.
elif isinstance(obj, torch.dtype):
return str(obj)
# JSON does NOT natively support numpy ty... | Extending python's JSON Encoder to serialize torch dtype. | default | python | oumi-ai/oumi | src/oumi/utils/serialization_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/serialization_utils.py | Apache-2.0 |
def convert_all_keys_to_serializable_types(dictionary: dict) -> None:
"""Converts all keys in a hierarchical dictionary to serializable types."""
serializable_key_types = {str, int, float, bool, None}
non_serializable_keys = [
key for key in dictionary if type(key) not in serializable_key_types
... | Converts all keys in a hierarchical dictionary to serializable types. | convert_all_keys_to_serializable_types | python | oumi-ai/oumi | src/oumi/utils/serialization_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/serialization_utils.py | Apache-2.0 |
def json_serializer(obj: Any) -> str:
"""Serializes a Python obj to a JSON formatted string."""
if dataclasses.is_dataclass(obj) and not isinstance(obj, type):
dict_to_serialize = dataclasses.asdict(obj)
elif isinstance(obj, dict):
dict_to_serialize = obj
else:
raise ValueError(f... | Serializes a Python obj to a JSON formatted string. | json_serializer | python | oumi-ai/oumi | src/oumi/utils/serialization_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/serialization_utils.py | Apache-2.0 |
def try_str_to_bool(s: str) -> Optional[bool]:
"""Attempts to convert a string representation to a boolean value.
This function interprets various string inputs as boolean values.
It is case-insensitive and recognizes common boolean representations.
Args:
s: The string to convert to a boolean.... | Attempts to convert a string representation to a boolean value.
This function interprets various string inputs as boolean values.
It is case-insensitive and recognizes common boolean representations.
Args:
s: The string to convert to a boolean.
Returns:
bool: The boolean interpretatio... | try_str_to_bool | python | oumi-ai/oumi | src/oumi/utils/str_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/str_utils.py | Apache-2.0 |
def str_to_bool(s: str) -> bool:
"""Convert a string representation to a boolean value.
This function interprets various string inputs as boolean values.
It is case-insensitive and recognizes common boolean representations.
Args:
s: The string to convert to a boolean.
Returns:
boo... | Convert a string representation to a boolean value.
This function interprets various string inputs as boolean values.
It is case-insensitive and recognizes common boolean representations.
Args:
s: The string to convert to a boolean.
Returns:
bool: The boolean interpretation of the inp... | str_to_bool | python | oumi-ai/oumi | src/oumi/utils/str_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/str_utils.py | Apache-2.0 |
def compute_utf8_len(s: str) -> int:
"""Computes string length in UTF-8 bytes."""
# This is inefficient: allocates a temporary copy of string content.
# FIXME Can we do better?
return len(s.encode("utf-8")) | Computes string length in UTF-8 bytes. | compute_utf8_len | python | oumi-ai/oumi | src/oumi/utils/str_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/str_utils.py | Apache-2.0 |
def get_editable_install_override_env_var() -> bool:
"""Returns whether OUMI_FORCE_EDITABLE_INSTALL env var is set to a truthy value."""
s = os.environ.get("OUMI_FORCE_EDITABLE_INSTALL", "")
mode = s.lower().strip()
bool_result = try_str_to_bool(mode)
if bool_result is not None:
return bool_... | Returns whether OUMI_FORCE_EDITABLE_INSTALL env var is set to a truthy value. | get_editable_install_override_env_var | python | oumi-ai/oumi | src/oumi/utils/str_utils.py | https://github.com/oumi-ai/oumi/blob/master/src/oumi/utils/str_utils.py | Apache-2.0 |
Subsets and Splits
Django Code with Docstrings
Filters Python code examples from Django repository that contain Django-related code, helping identify relevant code snippets for understanding Django framework usage patterns.
SQL Console for Shuu12121/python-treesitter-filtered-datasetsV2
Retrieves specific code examples from the Flask repository but doesn't provide meaningful analysis or patterns beyond basic data retrieval.
HTTPX Repo Code and Docstrings
Retrieves specific code examples from the httpx repository, which is useful for understanding how particular libraries are used but doesn't provide broader analytical insights about the dataset.
Requests Repo Docstrings & Code
Retrieves code examples with their docstrings and file paths from the requests repository, providing basic filtering but limited analytical value beyond finding specific code samples.
Quart Repo Docstrings & Code
Retrieves code examples with their docstrings from the Quart repository, providing basic code samples but offering limited analytical value for understanding broader patterns or relationships in the dataset.