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[PIR] Migrate paddle.static.nn.xx to paddle.nn.XX #2947

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Merged
merged 2 commits into from
Sep 13, 2024
Merged

[PIR] Migrate paddle.static.nn.xx to paddle.nn.XX #2947

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9754411
migrate static.nn.xx to nn.XX
changeyoung98 Sep 12, 2024
8f2b335
migrate static.nn.xx to nn.XX
changeyoung98 Sep 12, 2024
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10 changes: 3 additions & 7 deletions distributed/CE_API/case/dist_CountFilterEntry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,13 +33,9 @@ def test_CountFilterEntry():

input = paddle.static.data(name="ins", shape=[1], dtype="int64")

emb = paddle.static.nn.sparse_embedding(
input=input,
size=[sparse_feature_dim, embedding_size],
is_test=False,
entry=entry,
param_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()),
)
Emb = paddle.nn.Embedding(num_embeddings=sparse_feature_dim, embedding_dim=embedding_size, sparse=True,
weight_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()))
emb = Emb(input)
print(emb)
print("test_CountFilterEntry ... ok")

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10 changes: 3 additions & 7 deletions distributed/CE_API/case/dist_ProbabilityEntry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,13 +33,9 @@ def test_ProbabilityEntry():

input = paddle.static.data(name="ins", shape=[1], dtype="int64")

emb = paddle.static.nn.sparse_embedding(
input=input,
size=[sparse_feature_dim, embedding_size],
is_test=False,
entry=entry,
param_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()),
)
Emb = paddle.nn.Embedding(num_embeddings=sparse_feature_dim, embedding_dim=embedding_size, sparse=True,
weight_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()))
emb = Emb(input)
print(emb)
print("test_ProbabilityEntry ... ok")

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12 changes: 4 additions & 8 deletions distributed/CE_API/case/dist_ShowClickEntry.py
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Expand Up @@ -36,14 +36,10 @@ def test_ShowClickEntry():

entry = paddle.distributed.ShowClickEntry("show", "click")

emb = paddle.static.nn.sparse_embedding(
input=input,
size=[sparse_feature_dim, embedding_size],
is_test=False,
entry=entry,
param_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()),
)
assert emb.shape == (64,)
Emb = paddle.nn.Embedding(num_embeddings=sparse_feature_dim, embedding_dim=embedding_size, sparse=True,
weight_attr=paddle.ParamAttr(name="SparseFeatFactors", initializer=paddle.nn.initializer.Uniform()))
emb = Emb(input)
assert emb.shape == [1,64]

print("test_ShowClickEntry ... ok")

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5 changes: 3 additions & 2 deletions distributed/CE_API/case/dist_fleet_qat_init.py
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Expand Up @@ -37,8 +37,9 @@ def run_example_code():
exe = paddle.static.Executor(place)
# 1. Define the train program
data = paddle.static.data(name="X", shape=[None, 1, 28, 28], dtype="float32")
conv2d = paddle.static.nn.conv2d(input=data, num_filters=6, filter_size=3)
bn = paddle.static.nn.batch_norm(input=conv2d, act="relu")
Conv = paddle.nn.Conv2D(in_channels=1, out_channels=6, kernel_size=3)
conv2d = Conv(data)
bn = paddle.nn.BatchNorm2D(1)(conv2d)
pool = F.max_pool2d(bn, kernel_size=2, stride=2)
hidden = paddle.static.nn.fc(pool, size=10)
loss = paddle.mean(hidden)
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