From 948c57d84bcd127d01c4f1e992840116fc0be066 Mon Sep 17 00:00:00 2001 From: kinghuin Date: Sat, 4 Apr 2020 11:44:47 +0800 Subject: [PATCH] move sin, sqrt, tanh, atan to paddle.tensor.math and add a new parameter "out" (#23387) * sin sqrt tanh atan add out, test=develop * optimize doc, test=develop * add dygraph test, test=develop --- paddle/fluid/operators/activation_op.cc | 36 +++---- python/paddle/__init__.py | 8 +- .../tests/unittests/test_activation_op.py | 47 +++++++- python/paddle/tensor/__init__.py | 8 +- python/paddle/tensor/math.py | 101 ++++++++++++++++-- 5 files changed, 164 insertions(+), 36 deletions(-) diff --git a/paddle/fluid/operators/activation_op.cc b/paddle/fluid/operators/activation_op.cc index 9e329be9cc2..cfcb64732dc 100644 --- a/paddle/fluid/operators/activation_op.cc +++ b/paddle/fluid/operators/activation_op.cc @@ -169,14 +169,14 @@ $$out = \\log \\frac{1}{1 + e^{-x}}$$ UNUSED constexpr char ExpDoc[] = R"DOC( Exp Operator. Computes exp of x element-wise with a natural number :math:`e` as the base. -$out = e^x$ +$$out = e^x$$ )DOC"; UNUSED constexpr char ReluDoc[] = R"DOC( Relu Activation Operator. -$out = \max(x, 0)$ +$$out = \max(x, 0)$$ )DOC"; @@ -209,42 +209,42 @@ Rsqrt Activation Operator. Please make sure input is legal in case of numeric errors. -$out = \frac{1}{\sqrt{x}}$ +$$out = \frac{1}{\sqrt{x}}$$ )DOC"; UNUSED constexpr char AbsDoc[] = R"DOC( Abs Activation Operator. -$out = |x|$ +$$out = |x|$$ )DOC"; UNUSED constexpr char CeilDoc[] = R"DOC( Ceil Operator. Computes ceil of x element-wise. -$out = \left \lceil x \right \rceil$ +$$out = \left \lceil x \right \rceil$$ )DOC"; UNUSED constexpr char FloorDoc[] = R"DOC( Floor Activation Operator. -$out = \left \lfloor x \right \rfloor$ +$$out = \left \lfloor x \right \rfloor$$ )DOC"; UNUSED constexpr char CosDoc[] = R"DOC( Cosine Operator. Computes cosine of x element-wise. -$out = cos(x)$ +$$out = cos(x)$$ )DOC"; UNUSED constexpr char SinDoc[] = R"DOC( Sine Activation Operator. -$out = sin(x)$ +$$out = sin(x)$$ )DOC"; @@ -273,7 +273,7 @@ $$out = \\frac{1}{x}$$ UNUSED constexpr char LogDoc[] = R"DOC( Log Activation Operator. -$out = \ln(x)$ +$$out = \ln(x)$$ Natural logarithm of x. @@ -282,14 +282,14 @@ Natural logarithm of x. UNUSED constexpr char SquareDoc[] = R"DOC( The OP square each elements of the inputs. -$out = x^2$ +$$out = x^2$$ )DOC"; UNUSED constexpr char SoftplusDoc[] = R"DOC( Softplus Activation Operator. -$out = \ln(1 + e^{x})$ +$$out = \ln(1 + e^{x})$$ )DOC"; @@ -423,7 +423,7 @@ class BReluOpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( BRelu Activation Operator. -$out = \min(\max(x, t_{min}), t_{max})$ +$$out = \min(\max(x, t_{min}), t_{max})$$ )DOC"); } @@ -439,7 +439,7 @@ class SoftReluOpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( SoftRelu Activation Operator. -$out = \ln(1 + \exp(\max(\min(x, threshold), -threshold)))$ +$$out = \ln(1 + \exp(\max(\min(x, threshold), -threshold)))$$ )DOC"); } @@ -461,7 +461,7 @@ ELU Activation Operator. Applies the following element-wise computation on the input according to https://arxiv.org/abs/1511.07289. -$out = \max(0, x) + \min(0, \alpha * (e^x - 1))$ +$$out = \max(0, x) + \min(0, \alpha * (e^x - 1))$$ )DOC"); } @@ -482,7 +482,7 @@ class Relu6OpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( Relu6 Activation Operator. -$out = \min(\max(0, x), threshold)$ +$$out = \min(\max(0, x), threshold)$$ )DOC"); } @@ -502,7 +502,7 @@ class PowOpMaker : public framework::OpProtoAndCheckerMaker { AddComment(R"DOC( Pow Activation Operator. -$out = x^{factor}$ +$$out = x^{factor}$$ )DOC"); } @@ -568,7 +568,7 @@ HardSigmoid Activation Operator. A 3-part piecewise linear approximation of sigmoid(https://arxiv.org/abs/1603.00391), which is much faster than sigmoid. -$out = \max(0, \min(1, slope * x + offset))$ +$$out = \max(0, \min(1, slope * x + offset))$$ )DOC"); } @@ -608,7 +608,7 @@ HardSwish Activation Operator. The hard version of swish(https://arxiv.org/pdf/1905.02244.pdf). -$out = \frac{x * (min(max(0, x+offset), threshold))}{scale}$ +$$out = \frac{x * (min(max(0, x+offset), threshold))}{scale}$$ The threshold and scale should be positive. The offset can be either positive or negative. The default parameters are set according to the above reference. diff --git a/python/paddle/__init__.py b/python/paddle/__init__.py index 8d2ed9194d5..c8deb79c85a 100644 --- a/python/paddle/__init__.py +++ b/python/paddle/__init__.py @@ -92,7 +92,7 @@ from .tensor.logic import equal #DEFINE_ALIAS # from .tensor.math import abs #DEFINE_ALIAS # from .tensor.math import acos #DEFINE_ALIAS # from .tensor.math import asin #DEFINE_ALIAS -# from .tensor.math import atan #DEFINE_ALIAS +from .tensor.math import atan #DEFINE_ALIAS # from .tensor.math import ceil #DEFINE_ALIAS # from .tensor.math import cos #DEFINE_ALIAS # from .tensor.math import cumsum #DEFINE_ALIAS @@ -121,13 +121,13 @@ from .tensor.logic import equal #DEFINE_ALIAS # from .tensor.math import rsqrt #DEFINE_ALIAS # from .tensor.math import scale #DEFINE_ALIAS # from .tensor.math import sign #DEFINE_ALIAS -# from .tensor.math import sin #DEFINE_ALIAS -# from .tensor.math import sqrt #DEFINE_ALIAS +from .tensor.math import sin #DEFINE_ALIAS +from .tensor.math import sqrt #DEFINE_ALIAS # from .tensor.math import square #DEFINE_ALIAS # from .tensor.math import stanh #DEFINE_ALIAS # from .tensor.math import sum #DEFINE_ALIAS # from .tensor.math import sums #DEFINE_ALIAS -# from .tensor.math import tanh #DEFINE_ALIAS +from .tensor.math import tanh #DEFINE_ALIAS # from .tensor.math import elementwise_sum #DEFINE_ALIAS # from .tensor.math import max #DEFINE_ALIAS # from .tensor.math import min #DEFINE_ALIAS diff --git a/python/paddle/fluid/tests/unittests/test_activation_op.py b/python/paddle/fluid/tests/unittests/test_activation_op.py index 48aec26feac..428ec9ade8c 100644 --- a/python/paddle/fluid/tests/unittests/test_activation_op.py +++ b/python/paddle/fluid/tests/unittests/test_activation_op.py @@ -19,6 +19,7 @@ import numpy as np import paddle.fluid.core as core from op_test import OpTest from scipy.special import expit, erf +import paddle import paddle.fluid as fluid from paddle.fluid import compiler, Program, program_guard @@ -66,6 +67,36 @@ class TestActivation(OpTest): pass +class TestParameter(object): + def test_out(self): + with fluid.program_guard(fluid.Program()): + data = fluid.layers.data(name="X", shape=[1]) + out = eval("paddle.%s(data, out=data)" % self.op_type) + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result = exe.run(feed={"X": np.array([0.1])}, + fetch_list=[data, out]) + self.assertEqual(result[0], result[1]) + + def test_out_name(self): + with fluid.program_guard(fluid.Program()): + data = fluid.layers.data(name="X", shape=[1]) + out = eval("paddle.%s(data, name='Y', out=data)" % self.op_type) + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result = exe.run(feed={"X": np.array([0.1])}, + fetch_list=[data, out]) + self.assertEqual(result[0], result[1]) + + def test_dygraph(self): + with fluid.dygraph.guard(): + np_x = np.array([0.1]) + x = fluid.dygraph.to_variable(np_x) + z = eval("paddle.%s(x).numpy()" % self.op_type) + z_expected = eval("np.%s(np_x)" % self.op_type) + self.assertEqual(z, z_expected) + + class TestSigmoid(TestActivation): def setUp(self): self.op_type = "sigmoid" @@ -103,7 +134,7 @@ class TestLogSigmoid(TestActivation): self.check_grad(['X'], 'Out', max_relative_error=0.008) -class TestTanh(TestActivation): +class TestTanh(TestActivation, TestParameter): def setUp(self): self.op_type = "tanh" self.init_dtype() @@ -125,7 +156,7 @@ class TestTanh(TestActivation): self.dtype = np.float32 -class TestAtan(TestActivation): +class TestAtan(TestActivation, TestParameter): def setUp(self): self.op_type = "atan" self.init_dtype() @@ -141,6 +172,14 @@ class TestAtan(TestActivation): return self.check_grad(['X'], 'Out') + def test_dygraph(self): + with fluid.dygraph.guard(): + np_x = np.array([0.1]) + x = fluid.dygraph.to_variable(np_x) + z = paddle.atan(x).numpy() + z_expected = np.arctan(np_x) + self.assertEqual(z, z_expected) + class TestTanhShrink(TestActivation): def setUp(self): @@ -200,7 +239,7 @@ class TestSoftShrink(TestActivation): self.check_grad(['X'], 'Out') -class TestSqrt(TestActivation): +class TestSqrt(TestActivation, TestParameter): def setUp(self): self.op_type = "sqrt" self.init_dtype() @@ -324,7 +363,7 @@ class TestAcos(TestActivation): self.check_grad(['X'], 'Out') -class TestSin(TestActivation): +class TestSin(TestActivation, TestParameter): def setUp(self): self.op_type = "sin" self.init_dtype() diff --git a/python/paddle/tensor/__init__.py b/python/paddle/tensor/__init__.py index c578ee5386d..36b7868dba6 100644 --- a/python/paddle/tensor/__init__.py +++ b/python/paddle/tensor/__init__.py @@ -69,7 +69,7 @@ from .logic import equal #DEFINE_ALIAS # from .math import abs #DEFINE_ALIAS # from .math import acos #DEFINE_ALIAS # from .math import asin #DEFINE_ALIAS -# from .math import atan #DEFINE_ALIAS +from .math import atan #DEFINE_ALIAS # from .math import ceil #DEFINE_ALIAS # from .math import cos #DEFINE_ALIAS # from .math import cumsum #DEFINE_ALIAS @@ -98,13 +98,13 @@ from .logic import equal #DEFINE_ALIAS # from .math import rsqrt #DEFINE_ALIAS # from .math import scale #DEFINE_ALIAS # from .math import sign #DEFINE_ALIAS -# from .math import sin #DEFINE_ALIAS -# from .math import sqrt #DEFINE_ALIAS +from .math import sin #DEFINE_ALIAS +from .math import sqrt #DEFINE_ALIAS # from .math import square #DEFINE_ALIAS # from .math import stanh #DEFINE_ALIAS # from .math import sum #DEFINE_ALIAS # from .math import sums #DEFINE_ALIAS -# from .math import tanh #DEFINE_ALIAS +from .math import tanh #DEFINE_ALIAS # from .math import elementwise_sum #DEFINE_ALIAS # from .math import max #DEFINE_ALIAS # from .math import min #DEFINE_ALIAS diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index 9c04e62b164..082fe6063a5 100644 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -12,11 +12,22 @@ # See the License for the specific language governing permissions and # limitations under the License. -# TODO: define math functions -# __all__ = ['abs', +from __future__ import print_function + +import warnings + +from ..fluid.framework import OpProtoHolder, core, in_dygraph_mode +from ..fluid.layer_helper import LayerHelper +from ..fluid.data_feeder import check_variable_and_dtype +from ..fluid.layers.layer_function_generator import _generate_doc_string_ + +# TODO: define math functions +# yapf: disable +__all__ = [ +# 'abs', # 'acos', # 'asin', -# 'atan', + 'atan', # 'ceil', # 'cos', # 'cumsum', @@ -45,13 +56,13 @@ # 'rsqrt', # 'scale', # 'sign', -# 'sin', -# 'sqrt', + 'sin', + 'sqrt', # 'square', # 'stanh', # 'sum', # 'sums', -# 'tanh', + 'tanh', # 'elementwise_sum', # 'max', # 'min', @@ -65,3 +76,81 @@ # 'erf', # 'addcmul', # 'addmm'] +] +# yapf: enable. + + +def generate_op_noattr(op_type): + """Register the Python layer for an Operator without Attribute.. + + Args: + op_type: The name of the operator to be created. + + This function takes in the operator type (sin, tanh etc) and + creates the operator functionality. + + """ + op_proto = OpProtoHolder.instance().get_op_proto(op_type) + + def func(x, name=None, out=None): + if in_dygraph_mode(): + op = getattr(core.ops, op_type) + return op(x) + + check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], + op_type) + helper = LayerHelper(op_type, **locals()) + + if name and out: + warnings.warn( + "Both name and out parameters have been set in fluid.tensor.math.%s(), only out will take effect to specify the result storage. " + "You can discard either one to solve this warning." % op_type, + category=UserWarning, + stacklevel=2) + if not out: + out = helper.create_variable_for_type_inference(dtype=x.dtype) + helper.append_op(type=op_type, inputs={"X": x}, outputs={"Out": out}) + return out + + func.__name__ = op_type + func.__doc__ = _generate_doc_string_( + op_proto, + additional_args_lines=[ + "name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`.\n " + "out(Variable, optional): The default value is None. Optional output can be any created Variable that meets the requirements to store the result of operation. if out is None, a new Varibale will be create to store the result." + ]) + func.__doc__ = func.__doc__ + """ + +Return type + Variable +Examples: + .. code-block:: python + + import numpy as np + + import paddle + import paddle.fluid as fluid + + inputs = fluid.data(name="x", shape = [None, 4], dtype='float32') + output = paddle.%s(inputs) + + exe = fluid.Executor(fluid.CPUPlace()) + exe.run(fluid.default_startup_program()) + + #input.shape=1X4, batch_size=1 + img = np.array([[1.0, 2.0, 3.0, 4.0]]).astype(np.float32) + res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output]) + print(res) +""" % op_type + return func + + +__ops__noattr__ = [ + 'atan', + 'sin', + 'sqrt', + 'tanh', +] + +for _OP in set(__ops__noattr__): + globals()[_OP] = generate_op_noattr(_OP) -- GitLab