code stringlengths 3 6.57k |
|---|
module_state_dict() |
os.path.join(save_dir, tag) |
self.module_state_dict() |
self.optimizer.state_dict() |
self.zero_optimization() |
self.lr_scheduler.state_dict() |
state.update(client_state) |
log_dist(message=f'Saving model checkpoint: {save_path}', ranks=[0]) |
logger.info('Saving model checkpoint: {}'.format(save_path) |
torch.save(state, save_path) |
_get_param_shapes(self) |
OrderedDict() |
self.module.named_parameters() |
print(f"saving param {name} {param_shapes[name]}") |
_copy_recovery_script(self, save_path) |
os.path.dirname(os.path.dirname(__file__) |
os.path.join(base_dir, "utils", script) |
os.path.join(save_path, script) |
logger.info(f"creating recovery script {dst}") |
copyfile(src, dst) |
os.chmod(dst, os.stat(dst) |
_save_zero_checkpoint(self, save_path, tag) |
self._get_zero_ckpt_name(save_path, tag) |
self.optimizer.state_dict() |
self._get_param_shapes() |
torch.save(zero_sd, zero_checkpoint_name) |
self._copy_recovery_script(save_path) |
logger.info('zero checkpoint saved {}'.format(zero_checkpoint_name) |
_zero3_consolidated_fp16_state_dict(self) |
nn.Module.state_dict (modelled after _save_to_state_dict) |
self.zero_optimization_partition_weights() |
ValueError("this function requires ZeRO-3 mode") |
OrderedDict() |
torch.distributed.get_rank() |
get_layer_state_dict(module, prefix="") |
module.parameters(recurse=False) |
torch.distributed.get_rank() |
module.named_parameters(recurse=False) |
param.storage() |
data_ptr() |
print(f"`{key}` is shared with `{shared_weights[data_ptr_id]}`") |
param.detach() |
cpu() |
print(f"param {name} {param.shape}") |
print(f"param {key} {param.shape} {state_dict[key].storage() |
data_ptr() |
module.named_buffers(recurse=False) |
buf.detach() |
cpu() |
module.named_children() |
get_layer_state_dict(child, prefix + name + ".") |
see_memory_usage("before get_layer_state_dict", force=False) |
get_layer_state_dict(self.module, prefix="") |
see_memory_usage("after get_layer_state_dict", force=False) |
save_fp16_model(self, save_dir, save_filename="pytorch_model.bin") |
os.path.join(save_dir, save_filename) |
self.zero_optimization_partition_weights() |
self.zero_gather_fp16_weights_on_model_save() |
self._zero3_consolidated_fp16_state_dict() |
self.module.state_dict() |
torch.distributed.get_rank() |
os.makedirs(save_dir, exist_ok=True) |
logger.info(f"Saving model weights to {path}") |
torch.save(state_dict, path) |
np.random.RandomState(323) |
sr.StatsRecorder() |
np.empty((0, ndims) |
range(1000) |
rs.randint(10,101) |
rs.randn(nobserv, ndims) |
np.vstack((data, newdata) |
mystats.update(newdata) |
np.allclose(mystats.mean, data.mean(axis=0) |
np.allclose(mystats.std, data.std(axis=0) |
InsertPrimitiveDialog(QtWidgets.QWidget) |
__init__(self, primitive, parent) |
super() |
__init__(parent) |
self.parent.scenes.switchToSampleScene() |
QtWidgets.QVBoxLayout() |
self.parent_model.uniqueKey(self.primitive.value) |
self.mesh_args.update({'outer_radius': 100.000, 'inner_radius': 50.000, 'height': 200.000}) |
self.mesh_args.update({'radius': 100.000}) |
self.mesh_args.update({'radius': 100.000, 'height': 200.000}) |
self.mesh_args.update({'width': 50.000, 'height': 100.000, 'depth': 200.000}) |
self.createPrimitiveSwitcher() |
self.createFormInputs() |
QtWidgets.QHBoxLayout() |
QtWidgets.QPushButton('Create') |
self.create_primitive_button.clicked.connect(self.createPrimiviteButtonClicked) |
button_layout.addWidget(self.create_primitive_button) |
button_layout.addStretch(1) |
self.main_layout.addLayout(button_layout) |
self.main_layout.addStretch(1) |
self.setLayout(self.main_layout) |
format(self.primitive.value) |
self.setMinimumWidth(450) |
setFocus() |
createPrimitiveSwitcher(self) |
QtWidgets.QHBoxLayout() |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.