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[Cleanup][B-19]Replace to_variable #61545

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Feb 4, 2024
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[Cleanup][B-19]Replace to_variable #61545

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18 changes: 9 additions & 9 deletions python/paddle/amp/grad_scaler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,10 +18,10 @@

import numpy as np

import paddle
from paddle import _C_ops, _legacy_C_ops
from paddle.base import core
from paddle.base.data_feeder import check_type
from paddle.base.dygraph import to_variable
from paddle.base.framework import _dygraph_tracer, dygraph_only
from paddle.framework import in_dynamic_mode

Expand Down Expand Up @@ -130,20 +130,20 @@ def __init__(
self._decr_count = 0
self._use_dynamic_loss_scaling = use_dynamic_loss_scaling

self._found_inf = to_variable(np.array([0]).astype(np.bool_))
self._temp_found_inf_value_false = to_variable(
self._found_inf = paddle.to_tensor(np.array([0]).astype(np.bool_))
self._temp_found_inf_value_false = paddle.to_tensor(
np.array([0]).astype(np.bool_)
)
self._temp_found_inf_fp16 = to_variable(
self._temp_found_inf_fp16 = paddle.to_tensor(
np.array([0]).astype(np.bool_)
)
self._temp_found_inf_bf16 = to_variable(
self._temp_found_inf_bf16 = paddle.to_tensor(
np.array([0]).astype(np.bool_)
)
self._temp_found_inf_fp32 = to_variable(
self._temp_found_inf_fp32 = paddle.to_tensor(
np.array([0]).astype(np.bool_)
)
self._scale = to_variable(
self._scale = paddle.to_tensor(
np.array([self._init_loss_scaling]).astype(np.float32)
)
self._cache_founf_inf = None
Expand Down Expand Up @@ -438,7 +438,7 @@ def set_init_loss_scaling(self, new_init_loss_scaling):
new_init_loss_scaling(int): The new_init_loss_scaling used to update initial loss scaling factor.s
"""
self._init_loss_scaling = new_init_loss_scaling
self._scale = to_variable(
self._scale = paddle.to_tensor(
np.array([self._init_loss_scaling]).astype(np.float32)
)

Expand Down Expand Up @@ -563,7 +563,7 @@ def load_state_dict(self, state_dict):
)

self._init_loss_scaling = state_dict["scale"][0]
self._scale = to_variable(
self._scale = paddle.to_tensor(
np.array([self._init_loss_scaling]).astype(np.float32)
)
self._incr_ratio = state_dict["incr_ratio"]
Expand Down
8 changes: 4 additions & 4 deletions python/paddle/base/dygraph/tensor_patch_methods.py
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Expand Up @@ -94,12 +94,12 @@ def _to_static_var(self, to_parameter=False, **kwargs):
.. code-block:: python

>>> import paddle.base as base
>>> from paddle.base.dygraph.base import to_variable
>>> import paddle
>>> import numpy as np

>>> data = np.ones([3, 1024], dtype='float32')
>>> with base.dygraph.guard():
... tensor = to_variable(data)
... tensor = paddle.to_tensor(data)
... static_var = tensor._to_static_var()
"""

Expand Down Expand Up @@ -175,14 +175,14 @@ def set_value(self, value):
.. code-block:: python

>>> import paddle.base as base
>>> from paddle.base.dygraph.base import to_variable
>>> import paddle
>>> from paddle.nn import Linear
>>> import numpy as np

>>> data = np.ones([3, 1024], dtype='float32')
>>> with base.dygraph.guard():
... linear = Linear(1024, 4)
... t = to_variable(data)
... t = paddle.to_tensor(data)
... linear(t) # call with default weight
... custom_weight = np.random.randn(1024, 4).astype("float32")
... linear.weight.set_value(custom_weight) # change existing weight
Expand Down
18 changes: 9 additions & 9 deletions python/paddle/base/framework.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1505,9 +1505,10 @@ class Variable(metaclass=VariableMetaClass):

>>> import paddle.base as base
>>> import numpy as np
>>> import paddle

>>> with base.dygraph.guard():
... new_variable = base.dygraph.to_variable(np.arange(10))
... new_variable = paddle.to_tensor(np.arange(10))

"""

Expand Down Expand Up @@ -1693,14 +1694,13 @@ def numpy(self):
.. code-block:: python

>>> import paddle.base as base
>>> from paddle.base.dygraph.base import to_variable
>>> from paddle.nn import Linear
>>> import numpy as np

>>> data = np.random.uniform(-1, 1, [30, 10, 32]).astype('float32')
>>> with base.dygraph.guard():
... linear = Linear(32, 64)
... data = to_variable(data)
... data = paddle.to_tensor(data)
... x = linear(data)
... print(x.numpy())

Expand Down Expand Up @@ -1779,7 +1779,7 @@ def gradient(self):
>>> with base.dygraph.guard():
... inputs2 = []
... for _ in range(10):
... tmp = base.dygraph.base.to_variable(x)
... tmp = paddle.to_tensor(x)
... tmp.stop_gradient=False
... inputs2.append(tmp)
... ret2 = paddle.add_n(inputs2)
Expand All @@ -1797,7 +1797,7 @@ def gradient(self):
... sparse=True)
... x_data = np.arange(12).reshape(4, 3).astype('int64')
... x_data = x_data.reshape((-1, 3, 1))
... x = base.dygraph.base.to_variable(x_data)
... x = paddle.to_tensor(x_data)
... out = embedding(x)
... out.backward()
... print(embedding.weight.gradient())
Expand Down Expand Up @@ -1827,7 +1827,7 @@ def clear_gradient(self):
>>> x = np.ones([2, 2], np.float32)
>>> inputs2 = []
>>> for _ in range(10):
>>> tmp = base.dygraph.base.to_variable(x)
>>> tmp = paddle.to_tensor(x)
>>> tmp.stop_gradient=False
>>> inputs2.append(tmp)
>>> ret2 = paddle.add_n(inputs2)
Expand Down Expand Up @@ -2052,9 +2052,9 @@ def stop_gradient(self):
... value2 = np.arange(10).reshape(2, 5).astype("float32")
... linear = paddle.nn.Linear(13, 5)
... linear2 = paddle.nn.Linear(3, 3)
... a = base.dygraph.to_variable(value0)
... b = base.dygraph.to_variable(value1)
... c = base.dygraph.to_variable(value2)
... a = paddle.to_tensor(value0)
... b = paddle.to_tensor(value1)
... c = paddle.to_tensor(value2)
... out1 = linear(a)
... out2 = linear2(b)
... out1.stop_gradient = True
Expand Down
3 changes: 2 additions & 1 deletion python/paddle/base/layers/math_op_patch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -326,11 +326,12 @@ def astype(self, dtype):
.. code-block:: python

>>> import paddle.base as base
>>> import paddle
>>> import numpy as np

>>> x = np.ones([2, 2], np.float32)
>>> with base.dygraph.guard():
... original_variable = base.dygraph.to_variable(x)
... original_variable = paddle.to_tensor(x)
... print("original var's dtype is: {}, numpy dtype is {}".format(original_variable.dtype, original_variable.numpy().dtype))
... new_variable = original_variable.astype('int64')
... print("new var's dtype is: {}, numpy dtype is {}".format(new_variable.dtype, new_variable.numpy().dtype))
Expand Down
7 changes: 3 additions & 4 deletions python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_utils.py
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Expand Up @@ -21,7 +21,6 @@
import paddle
from paddle import _C_ops, _legacy_C_ops
from paddle.base import core
from paddle.base.dygraph import to_variable
from paddle.common_ops_import import dygraph_only
from paddle.nn import clip

Expand Down Expand Up @@ -278,9 +277,9 @@ def unscale_method(self, optimizer):
else:
param_grads_fp32.append(tgt_grad)

temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool_))
temp_found_inf_bfp16 = to_variable(np.array([0]).astype(np.bool_))
temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool_))
temp_found_inf_fp16 = paddle.to_tensor(np.array([0]).astype(np.bool_))
temp_found_inf_bfp16 = paddle.to_tensor(np.array([0]).astype(np.bool_))
temp_found_inf_fp32 = paddle.to_tensor(np.array([0]).astype(np.bool_))

device = paddle.get_device().split(":")[0]
device = "cpu" if optimizer.offload else device
Expand Down
3 changes: 1 addition & 2 deletions python/paddle/distributed/fleet/utils/mix_precision_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,6 @@
from paddle.base import framework
from paddle.base.dygraph import (
base as imperative_base,
to_variable,
)
from paddle.distributed import fleet
from paddle.distributed.fleet.utils.hybrid_parallel_util import (
Expand Down Expand Up @@ -215,7 +214,7 @@ def unscale_method(self, optimizer):
assert param.main_grad.dtype == core.VarDesc.VarType.FP32
param_grads.append(param.main_grad)

temp_found_inf = to_variable(np.array([0]).astype(np.bool_))
temp_found_inf = paddle.to_tensor(np.array([0]).astype(np.bool_))
if len(param_grads):
_legacy_C_ops.check_finite_and_unscale(
param_grads,
Expand Down