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support env var CPU_USE_NUMPY #2176

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Merged
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Sep 23, 2025
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support env var CPU_USE_NUMPY #2176

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1 change: 1 addition & 0 deletions mindnlp/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,3 +30,4 @@
from . import transformers
from . import diffusers

__version__ = '0.5.0rc2'
12 changes: 12 additions & 0 deletions mindtorch/_apis/npu.py
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Expand Up @@ -1566,6 +1566,12 @@ def flash_attention_score(query, key, value, real_shift, drop_mask, padding_mask
return pyboost.flash_attention_score_impl(query, key, value, real_shift, drop_mask, padding_mask, attn_mask, prefix, actual_seq_qlen, actual_seq_kvlen, head_num, keep_prob, scale_value, pre_tokens, next_tokens, inner_precise, input_layout, sparse_mode)
return legacy.flash_attention_score(query, key, value, real_shift, drop_mask, padding_mask, attn_mask, prefix, actual_seq_qlen, actual_seq_kvlen, head_num, keep_prob, scale_value, pre_tokens, next_tokens, inner_precise, input_layout, sparse_mode)

def prompt_flash_attention(query, key, value, attn_mask, actual_seq_lengths, actual_seq_lengths_kv, pse_shift, deq_scale1, quant_scale1, deq_scale2, quant_scale2, quant_offset2, num_heads, scale_value, pre_tokens, next_tokens, input_layout, num_key_value_heads, sparse_mode, inner_precise):
return pyboost.prompt_flash_attention_impl(query, key, value, attn_mask, actual_seq_lengths, actual_seq_lengths_kv, pse_shift, deq_scale1, quant_scale1, deq_scale2, quant_scale2, quant_offset2, num_heads, scale_value, pre_tokens, next_tokens, input_layout, num_key_value_heads, sparse_mode, inner_precise)

def incre_flash_attention(query, key, value, attn_mask, actual_seq_lengths, pse_shift, dequant_scale1, quant_scale1, dequant_scale2, quant_scale2, quant_offset2, antiquant_scale, antiquant_offset, block_table, kv_padding_size, num_heads, input_layout, scale_value, num_key_value_heads, block_size, inner_precise):
return pyboost.incre_flash_attention_impl(query, key, value, attn_mask, actual_seq_lengths, pse_shift, dequant_scale1, quant_scale1, dequant_scale2, quant_scale2, quant_offset2, antiquant_scale, antiquant_offset, block_table, kv_padding_size, num_heads, input_layout, scale_value, num_key_value_heads, block_size, inner_precise)

def randperm(n, generator, dtype):
seed, offset = generator._step(12) # pylint: disable=protected-access
if use_pyboost():
Expand Down Expand Up @@ -1617,3 +1623,9 @@ def new_ones(input, size, dtype):

def kl_div(input, target, reduction, log_target):
return pyboost.kl_div_op(input, target, reduction, log_target)

def repeat_interleave_int(input, repeats, dim, output_size):
return pyboost.repeat_interleave_int_op(input, repeats, dim, output_size)

def repeat_interleave_tensor(input, repeats, dim, output_size):
return pyboost.repeat_interleave_tensor_op(input, repeats, dim, output_size)
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