Method backward

src/transformers/integrations/bitnet.py:252–254 · view source on GitHub ↗

(ctx, grad_output)

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250
251	@staticmethod
252	def backward(ctx, grad_output):
253	grad_input = grad_output.clone()
254	return grad_input
255
256
257	class AutoBitLinear(nn.Linear):

smp_forward_backwardFunction · 0.45

training_stepMethod · 0.45

test_enable_input_require_grads_with_gradient_checkpointingMethod · 0.45

check_training_gradient_checkpointingMethod · 0.45

test_trainingMethod · 0.45

test_retain_grad_hidden_states_attentionsMethod · 0.45

test_problem_typesMethod · 0.45

test_flash_attn_2_can_compile_with_attention_mask_None_without_graph_breakMethod · 0.45

test_torch_compile_for_trainingMethod · 0.45

_test_tp_backward_implFunction · 0.45

_test_ep_backward_implFunction · 0.45

test_training_overfitMethod · 0.45

no outgoing calls

test_enable_input_require_grads_with_gradient_checkpointingMethod · 0.36

check_training_gradient_checkpointingMethod · 0.36

test_trainingMethod · 0.36

test_retain_grad_hidden_states_attentionsMethod · 0.36

test_problem_typesMethod · 0.36

test_flash_attn_2_can_compile_with_attention_mask_None_without_graph_breakMethod · 0.36

test_torch_compile_for_trainingMethod · 0.36

_test_tp_backward_implFunction · 0.36

_test_ep_backward_implFunction · 0.36

test_training_overfitMethod · 0.36

test_trainingMethod · 0.36