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update ts export infer #525

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Sep 6, 2024
Merged

update ts export infer #525

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71 changes: 42 additions & 29 deletions paddlets/models/anomaly/dl/anomaly_base.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -766,7 +766,8 @@ def save(self,
path: str,
network_model: bool=False,
dygraph_to_static: bool=True,
batch_size: Optional[int]=None) -> None:
batch_size: Optional[int]=None,
data_info: Optional[dict]=None) -> None:
"""
Saves a AnomalyBaseModel instance to a disk file.

Expand Down Expand Up @@ -872,17 +873,27 @@ def save(self,
% (internal_filename_map["network_model"], str(e))))

# 2 save model meta (e.g. classname)
try:
with open(
os.path.join(abs_root_path,
internal_filename_map["model_meta"]),
"w") as f:
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))
try:
with open(os.path.join(abs_root_path, 'inference.yml'), "w") as f:
if data_info is not None:
model_meta.update(data_info)
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))

if not network_model:
try:
with open(
os.path.join(abs_root_path,
internal_filename_map["model_meta"]),
"w") as f:
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))
# 3 save optimizer state dict (currently ignore optimizer logic.)
# optimizer_state_dict = self._optimizer.state_dict()
# try:
Expand All @@ -899,17 +910,18 @@ def save(self,
# )

# 4 save network state dict
network_state_dict = self._network.state_dict()
try:
paddle.save(
obj=network_state_dict,
path=os.path.join(abs_root_path,
internal_filename_map["network_statedict"]))
except Exception as e:
raise_log(
ValueError("error occurred while saving %s: %s, err: %s" %
(internal_filename_map["network_statedict"],
network_state_dict, str(e))))
if not network_model:
network_state_dict = self._network.state_dict()
try:
paddle.save(
obj=network_state_dict,
path=os.path.join(abs_root_path,
internal_filename_map["network_statedict"]))
except Exception as e:
raise_log(
ValueError("error occurred while saving %s: %s, err: %s" %
(internal_filename_map["network_statedict"],
network_state_dict, str(e))))

# 5 save model
optimizer = self._optimizer
Expand All @@ -927,13 +939,14 @@ def save(self,
# loss_fn could possibly contain paddle.Tensor when it is a bound method of a class, thus needs to set to
# None to avoid pickle.dumps failure.
self._loss_fn = None
try:
with open(abs_model_path, "wb") as f:
pickle.dump(self, f)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
abs_model_path, str(e))))
if not network_model:
try:
with open(abs_model_path, "wb") as f:
pickle.dump(self, f)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
abs_model_path, str(e))))

# in order to allow a model instance to be saved multiple times, set attrs back.
self._optimizer = optimizer
Expand Down
13 changes: 7 additions & 6 deletions paddlets/models/base_model/_timesnet/timesblock.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ def FFT_for_Period(x, k=2):
frequency_list[0] = 0
_, top_list = paddle.topk(x=frequency_list, k=k) # 幅度最大的前k个
top_list = top_list.detach().cast('int32')
period = x.shape[1] // top_list.cpu().numpy() # 长度/频率=周期
period = paddle.shape(x)[1] // top_list # 长度/频率=周期
return period, xf.abs().mean(axis=-1).index_select(
index=top_list, axis=1) # 幅值最大的几个频率项

Expand All @@ -26,6 +26,7 @@ def __init__(
super(TimesBlock, self).__init__()
self.seq_len = in_chunk_len
self.pred_len = out_chunk_len
self.seq_pred_len = paddle.to_tensor(self.seq_len + self.pred_len)
self.k = top_k
self.conv = nn.Sequential(
Inception_Block_V1(
Expand All @@ -41,15 +42,15 @@ def forward(self, x):
res = []
for i in range(self.k):
period = period_list[i]
if (self.seq_len + self.pred_len) % period != 0:
length = ((self.seq_len + self.pred_len) // period + 1) * period
if self.seq_pred_len % period != 0:
length = (self.seq_pred_len // period + 1) * period
padding = paddle.zeros(shape=[
x.shape[0], length - (self.seq_len + self.pred_len),
x.shape[0], length - self.seq_pred_len,
x.shape[2]
])
out = paddle.concat(x=[x, padding], axis=1)
out = paddle.concat(x=[x.cast('float32'), padding.cast('float32')], axis=1)
else:
length = self.seq_len + self.pred_len
length = self.seq_pred_len
out = x

out = out.reshape([B, length // period, period, N]).transpose(
Expand Down
5 changes: 4 additions & 1 deletion paddlets/models/classify/dl/adapter/paddle_dataset_impl.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -100,7 +100,10 @@ def format_labels(self, labels):
self.classes_ = self.label_encoder.classes_
self.n_classes_ = len(self.classes_)
y = y.reshape(len(y), 1)
self.onehot_encoder = OneHotEncoder(sparse=False, categories="auto")
try:
self.onehot_encoder = OneHotEncoder(sparse=False, categories="auto")
except:
self.onehot_encoder = OneHotEncoder(sparse_output=False, categories="auto")
y = self.onehot_encoder.fit_transform(y).astype(np.float32)
return y

Expand Down
75 changes: 44 additions & 31 deletions paddlets/models/classify/dl/paddle_base.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -628,7 +628,8 @@ def save(self,
path: str,
network_model: bool=False,
dygraph_to_static=True,
batch_size: Optional[int]=None) -> None:
batch_size: Optional[int]=None,
data_info: Optional[dict]=None) -> None:
"""
Saves a PaddleBaseClassifier instance to a disk file.

Expand Down Expand Up @@ -713,30 +714,40 @@ def save(self,
% (internal_filename_map["network_model"], str(e))))

# 2 save model meta (e.g. classname)
try:
with open(
os.path.join(abs_root_path,
internal_filename_map["model_meta"]),
"w") as f:
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))
try:
with open(os.path.join(abs_root_path, 'inference.yml'), "w") as f:
if data_info is not None:
model_meta.update(data_info)
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))

if not network_model:
try:
with open(
os.path.join(abs_root_path,
internal_filename_map["model_meta"]),
"w") as f:
json.dump(model_meta, f, ensure_ascii=False)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
internal_filename_map["model_meta"], str(e))))
# 3 save network state dict
network_state_dict = self._network.state_dict()
try:
paddle.save(
obj=network_state_dict,
path=os.path.join(abs_root_path,
internal_filename_map["network_statedict"]),
)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s: %s, err: %s" %
(internal_filename_map["network_statedict"],
network_state_dict, str(e))))
if not network_model:
network_state_dict = self._network.state_dict()
try:
paddle.save(
obj=network_state_dict,
path=os.path.join(abs_root_path,
internal_filename_map["network_statedict"]), )
except Exception as e:
raise_log(
ValueError("error occurred while saving %s: %s, err: %s" %
(internal_filename_map["network_statedict"],
network_state_dict, str(e))))

# 4 save model
optimizer = self._optimizer
Expand All @@ -754,13 +765,14 @@ def save(self,
# loss_fn could possibly contain paddle.Tensor when it is a bound method of a class, thus needs to set to
# None to avoid pickle.dumps failure.
self._loss_fn = None
try:
with open(abs_model_path, "wb") as f:
pickle.dump(self, f)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
abs_model_path, str(e))))
if not network_model:
try:
with open(abs_model_path, "wb") as f:
pickle.dump(self, f)
except Exception as e:
raise_log(
ValueError("error occurred while saving %s, err: %s" % (
abs_model_path, str(e))))

# in order to allow a model instance to be saved multiple times, set attrs back.
self._optimizer = optimizer
Expand Down Expand Up @@ -836,7 +848,8 @@ def _build_meta(self):
"features": [
None, self._fit_params["input_lens"],
self._fit_params["feature_dim"]
]
],
"pad_mask": [None, self._fit_params["input_lens"]]
},
}

Expand Down
7 changes: 7 additions & 0 deletions paddlets/models/forecasting/dl/Nonstationary.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,8 @@ def __init__(self,
DSAttention(
False,
factor,
d_model,
n_heads,
attention_dropout=dropout,
output_attention=output_attention),
d_model,
Expand All @@ -138,6 +140,8 @@ def __init__(self,
DSAttention(
True,
factor,
d_model,
n_heads,
attention_dropout=dropout,
output_attention=False),
d_model,
Expand All @@ -146,6 +150,8 @@ def __init__(self,
DSAttention(
False,
factor,
d_model,
n_heads,
attention_dropout=dropout,
output_attention=False),
d_model,
Expand Down Expand Up @@ -183,6 +189,7 @@ def forward(self,
dec_self_mask=None,
dec_enc_mask=None):
x_enc = x["past_target"]

times_mark = x.get("known_cov_numeric", None)
x_mark_enc = times_mark[:, :self.seq_len, :]
dec_inp = paddle.zeros(shape=[x_enc.shape[0], self.pred_len, self.c_in])
Expand Down
6 changes: 6 additions & 0 deletions paddlets/models/forecasting/dl/TimesNet.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -256,6 +256,12 @@ def _update_fit_params(
"known_cov_dim": 0,
"observed_cov_dim": 0
}
if train_tsdataset[0].get_known_cov() is not None:
fit_params["known_cov_dim"] = train_tsdataset[0].get_known_cov(
).data.shape[1]
if train_tsdataset[0].get_observed_cov() is not None:
fit_params["observed_cov_dim"] = train_tsdataset[
0].get_observed_cov().data.shape[1]
return fit_params

@revin_norm # aligned? not used seemly
Expand Down
7 changes: 5 additions & 2 deletions paddlets/models/forecasting/dl/_nonstationary/MHSA_Family.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,11 +16,14 @@ class DSAttention(paddle.nn.Layer):
def __init__(self,
mask_flag=True,
factor=5,
d_model=128,
num_heads=8,
scale=None,
attention_dropout=0.1,
output_attention=False):
super(DSAttention, self).__init__()
self.scale = scale
E = d_model // num_heads
self.scale = scale if scale is not None else 1.0 / sqrt(E)
self.mask_flag = mask_flag
self.output_attention = output_attention
self.dropout = paddle.nn.Dropout(p=attention_dropout)
Expand All @@ -29,7 +32,7 @@ def __init__(self,
def forward(self, queries, keys, values, attn_mask, tau=None, delta=None):
B, L, H, E = queries.shape
_, S, _, D = values.shape
scale = self.scale or 1.0 / sqrt(E)
scale = self.scale
tau = 1.0 if tau is None else tau.unsqueeze(axis=1).unsqueeze(axis=1)
delta = 0.0 if delta is None else delta.unsqueeze(axis=1).unsqueeze(
axis=1)
Expand Down
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