From 2e1040fc3af3611063f8355cb36860eb1d504c99 Mon Sep 17 00:00:00 2001 From: songmingyang001 Date: Tue, 26 Aug 2025 13:47:43 +0000 Subject: [PATCH 1/2] !3018 add embedding hash table api Merge pull request !3018 from songmingyang001/ge_dev --- .../python/npu_bridge/npu_cpu/npu_cpu_ops.py | 101 ++++++++++++++++++ 1 file changed, 101 insertions(+) diff --git a/tf_adapter/python/npu_bridge/npu_cpu/npu_cpu_ops.py b/tf_adapter/python/npu_bridge/npu_cpu/npu_cpu_ops.py index e5abba177..64c0a221e 100644 --- a/tf_adapter/python/npu_bridge/npu_cpu/npu_cpu_ops.py +++ b/tf_adapter/python/npu_bridge/npu_cpu/npu_cpu_ops.py @@ -25,6 +25,29 @@ from npu_bridge.helper import helper gen_npu_cpu_ops = helper.get_gen_ops() +## 提供device侧FeatureMapping LookupOrInsert功能 +# @param table_handle int64 类型 +# @param keys int64 类型 +# @param bucket_size int 类型 +# @param embedding_dim int 类型 +# @param filter_mode string 类型 +# @param filter_freq int 类型 +# @param default_key_or_value bool 类型 +# @param default_key int 类型 +# @param default_value float 类型 +# @param filter_key_flag bool 类型 +# @param filter_key int 类型 +# @return values float 类型 +def embedding_hashtable_lookup_or_insert(table_handle, keys, bucket_size, embedding_dim, filter_mode, filter_freq, + default_key_or_value, default_key, default_value, filter_key_flag, filter_key): + """ device embedding feature mapping lookup or insert. """ + result = gen_npu_cpu_ops.EmbeddingHashTableLookupOrInsert( + table_handle=table_handle, keys=keys, bucket_size=bucket_size, embedding_dim=embedding_dim, + filter_mode=filter_mode, filter_freq=filter_freq, default_key_or_value=default_key_or_value, + default_key=default_key, default_value=default_value, filter_key_flag=filter_key_flag, filter_key=filter_key) + return result + + ## 提供embeddingrankid功能 # @param addr_tensor tensorflow的tensor类型，embeddingrankid操作的输入； # @param index tensorflow的tensor类型，embeddingrankid操作的输入； @@ -467,4 +490,82 @@ def embedding_hashmap_import_v2(file_path, table_ids, table_sizes, table_names, result = gen_npu_cpu_ops.EmbeddingHashmapImport( file_path=file_path, table_ids=table_ids, table_sizes=table_sizes, table_names=table_names, global_step=global_step, embedding_dims=embedding_dims, num=num) + return result + + +## EmbeddingHashTable Init功能 +# @param table_handle int64 类型 +# @param sampled_values float 类型 +# @param bucket_size int 类型 +# @param embedding_dim int 类型 +# @param initializer_mode string 类型 +# @param constant_value int 类型 +def init_embedding_hashtable(table_handle, sampled_values, bucket_size, embedding_dim, initializer_mode, + constant_value): + """ device init embedding hashtable. """ + result = gen_npu_cpu_ops.InitEmbeddingHashTable( + table_handle=table_handle, sampled_values=sampled_values, bucket_size=bucket_size, embedding_dim=embedding_dim, + initializer_mode=initializer_mode, constant_value=constant_value) + return result + + +## 提供host侧hashTable导入功能 +# @param table_handles int64 类型 +# @param embedding_dims int64 类型 +# @param bucket_sizes int64 类型 +# @param keys int64 类型 +# @param counters uint64 类型 +# @param filter_flags uint8 类型 +# @param values float 类型 +def embedding_hash_table_import(table_handles, embedding_dims, bucket_sizes, keys, counters, filter_flags, values): + """ host embedding feature hash table import. """ + result = gen_npu_cpu_ops.EmbeddingHashTableImport( + table_handles=table_handles, embedding_dims=embedding_dims, bucket_sizes=bucket_sizes, + keys=keys, counters=counters, filter_flags=filter_flags, values=values) + return result + + +## 提供host侧hashTable导出功能 +# @param table_handles int64 类型 +# @param table_sizes int64 类型 +# @param embedding_dims int64 类型 +# @param bucket_sizes int64 类型 +# @param export_mode string 类型 +# @param filtered_export_flag bool 类型 +def embedding_hash_table_export(table_handles, table_sizes, embedding_dims, bucket_sizes, export_mode='all', + filter_export_flag=False): + """ host embedding feature hash table export. """ + result = gen_npu_cpu_ops.EmbeddingHashTableExport( + table_handles=table_handles, table_sizes=table_sizes, embedding_dims=embedding_dims, bucket_sizes=bucket_sizes, + export_mode=export_mode, filter_export_flag=filter_export_flag) + return result + + +## EmbeddingHashTableApplyAdamW AdamW 更新功能 +# @param table_handle int64 类型 +# @param keys int64 类型 +# @param m float16, float32 类型 +# @param v float16, float32 类型 +# @param beta1_power float16, float32 类型 +# @param beta2_power float16, float32 类型 +# @param lr float16, float32 类型 +# @param weight_decay float16, float32 类型 +# @param beta1 float16, float32 类型 +# @param beta2 float16, float32 类型 +# @param epsilon float16, float32 类型 +# @param grad float16, float32 类型 +# @param max_grad_norm float16, float32 类型 +# @param embedding_dim int 类型 +# @param bucket_size int 类型 +# @param amsgrad bool 类型 +# @param maximize bool 类型 +def embedding_hashtable_apply_adam_w(table_handle, keys, m, v, beta1_power, beta2_power, lr, weight_decay, + beta1, beta2, epsilon, grad, max_grad_norm, embedding_dim, + bucket_size, amsgrad, maximize): + """ device update embedding hashtable using AdamW. """ + result = gen_npu_cpu_ops.EmbeddingHashTableApplyAdamW( + table_handle=table_handle, keys=keys, m=m, v=v, beta1_power=beta1_power, beta2_power=beta2_power, + lr=lr, weight_decay=weight_decay, beta1=beta1, beta2=beta2, epsilon=epsilon, grad=grad, + max_grad_norm=max_grad_norm, embedding_dim=embedding_dim, bucket_size=bucket_size, + amsgrad=amsgrad, maximize=maximize) return result \ No newline at end of file -- Gitee From a9c166f7867e328ea4c2be996cb3d22a20180f44 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=88=98=E5=BC=BA?= Date: Tue, 26 Aug 2025 14:09:02 +0000 Subject: [PATCH 2/2] =?UTF-8?q?!3017=20af=20core=20num=20api=20modify=20Me?= =?UTF-8?q?rge=20pull=20request=20!3017=20from=20=E5=88=98=E5=BC=BA/corenu?= =?UTF-8?q?maf?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- tf_adapter/python/npu_bridge/estimator/npu/npu_scope.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tf_adapter/python/npu_bridge/estimator/npu/npu_scope.py b/tf_adapter/python/npu_bridge/estimator/npu/npu_scope.py index 20547f587..d85e373d4 100644 --- a/tf_adapter/python/npu_bridge/estimator/npu/npu_scope.py +++ b/tf_adapter/python/npu_bridge/estimator/npu/npu_scope.py @@ -223,16 +223,16 @@ def disable_autofuse(): @contextlib.contextmanager def limit_core_num_scope(op_aicore_num="0", op_vectorore_num="0"): """ - Limit the aic abd aiv core num of autofuse operators within the scope. + Limit the aic and aiv core num of autofuse operators within the scope, only support aiv core num now. """ if not isinstance(op_vectorore_num, str): raise ValueError("Param op_vectorore_num must be string.") try: int_vector_core_num = int(op_vectorore_num) except ValueError: - raise ValueError("Param op_vectorore_num can not be translated into a valid int number.") - if not (0 < int_vector_core_num < 48): - raise ValueError("Param op_vectorore_num must be in a valid range.") + raise ValueError("Param op_vectorore_num can not be converted into a valid int number.") + if int_vector_core_num <= 0: + raise ValueError("Param op_vectorore_num must be greater than zero.") attrs = { "_op_vectorcore_num": attr_value_pb2.AttrValue(s=compat.as_bytes(op_vectorore_num)) } -- Gitee