forked from mindspore-Ecosystem/mindspore
update sponge
This commit is contained in:
zhangxinfeng3
parent
885177769a
commit
e1c277cdc5
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@ -18,6 +18,7 @@
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from ..primitive import PrimitiveWithInfer, prim_attr_register
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from ..._checkparam import Validator as validator
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from ...common import dtype as mstype
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from ..._checkparam import Rel
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class BondForce(PrimitiveWithInfer):
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@ -50,12 +51,30 @@ class BondForce(PrimitiveWithInfer):
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``GPU``
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Examples:
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"""
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@prim_attr_register
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def __init__(self, bond_numbers):
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self.bond_numbers = bond_numbers
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self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'bond_k', 'bond_r0'],
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outputs=['frc_f'])
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self.add_prim_attr('bond_numbers', self.bond_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, bond_k_shape, bond_r0_shape):
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cls_name = self.name
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# N = uint_crd_f_shape[0]
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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bond_k_shape[0], M, Rel.EQ, "bond_k_shape", cls_name)
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validator.check_int(
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bond_r0_shape[0], M, Rel.EQ, "bond_r0_shape", cls_name)
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return uint_crd_f_shape
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, bond_k_type, bond_r0_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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validator.check_tensor_dtype_valid('scaler_f_type', scaler_f_type, [mstype.float32], self.name)
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@ -81,6 +100,11 @@ class BondEnergy(PrimitiveWithInfer):
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Inputs:
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Same as operator BondForce().
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.. math::
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dr = (x_1-x_2, y_1-y_2, z_1-z_2)
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E = k*(|dr| - r_0)^2
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Outputs:
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- **bond_ene** (Tensor, float32) - [M, 1], the harmonic potential energy
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for each bond.
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@ -89,12 +113,31 @@ class BondEnergy(PrimitiveWithInfer):
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``GPU``
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Examples:
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"""
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@prim_attr_register
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def __init__(self, bond_numbers):
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self.bond_numbers = bond_numbers
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self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'bond_k', 'bond_r0'],
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outputs=['bond_ene'])
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self.add_prim_attr('bond_numbers', self.bond_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, bond_k_shape, bond_r0_shape):
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cls_name = self.name
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# N = uint_crd_f_shape[0]
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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bond_k_shape[0], M, Rel.EQ, "bond_k_shape", cls_name)
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validator.check_int(
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bond_r0_shape[0], M, Rel.EQ, "bond_r0_shape", cls_name)
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return bond_k_shape
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, bond_k_type, bond_r0_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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validator.check_tensor_dtype_valid('scaler_f_type', scaler_f_type, [mstype.float32], self.name)
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@ -125,12 +168,30 @@ class BondAtomEnergy(PrimitiveWithInfer):
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``GPU``
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Examples:
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"""
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@prim_attr_register
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def __init__(self, bond_numbers):
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self.bond_numbers = bond_numbers
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self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'bond_k', 'bond_r0'],
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outputs=['atom_ene'])
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self.add_prim_attr('bond_numbers', self.bond_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, bond_k_shape, bond_r0_shape):
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cls_name = self.name
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N = uint_crd_f_shape[0]
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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bond_k_shape[0], M, Rel.EQ, "bond_k_shape", cls_name)
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validator.check_int(
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bond_r0_shape[0], M, Rel.EQ, "bond_r0_shape", cls_name)
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return [N,]
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, bond_k_type, bond_r0_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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validator.check_tensor_dtype_valid('scaler_f_type', scaler_f_type, [mstype.float32], self.name)
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@ -167,13 +228,28 @@ class BondForceWithAtomEnergy(PrimitiveWithInfer):
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self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'bond_k', 'bond_r0'],
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outputs=['frc_f', 'atom_e'])
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self.add_prim_attr('bond_numbers', self.bond_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, bond_k_shape, bond_r0_shape):
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cls_name = self.name
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N = uint_crd_f_shape[0]
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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bond_k_shape[0], M, Rel.EQ, "bond_k_shape", cls_name)
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validator.check_int(
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bond_r0_shape[0], M, Rel.EQ, "bond_r0_shape", cls_name)
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return uint_crd_f_shape, [N,]
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, bond_k_type, bond_r0_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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validator.check_tensor_dtype_valid('scaler_f_type', scaler_f_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('atom_a_type', atom_a_type, [mstype.int32], self.name)
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validator.check_tensor_dtype_valid('atom_b_type', atom_b_type, [mstype.int32], self.name)
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validator.check_tensor_dtype_valid('bond_k_type', bond_k_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('bond_r0_type', bond_r0_type, [mstype.float32], self.name)
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return bond_r0_type, bond_r0_type
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@ -213,17 +289,33 @@ class BondForceWithAtomVirial(PrimitiveWithInfer):
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self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'bond_k', 'bond_r0'],
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outputs=['frc_f', 'atom_v'])
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self.add_prim_attr('bond_numbers', self.bond_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, bond_k_shape, bond_r0_shape):
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cls_name = self.name
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N = uint_crd_f_shape[0]
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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bond_k_shape[0], M, Rel.EQ, "bond_k_shape", cls_name)
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validator.check_int(
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bond_r0_shape[0], M, Rel.EQ, "bond_r0_shape", cls_name)
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return uint_crd_f_shape, [N,]
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, bond_k_type, bond_r0_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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validator.check_tensor_dtype_valid('scaler_f_type', scaler_f_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('atom_a_type', atom_a_type, [mstype.int32], self.name)
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validator.check_tensor_dtype_valid('atom_b_type', atom_b_type, [mstype.int32], self.name)
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validator.check_tensor_dtype_valid('bond_k_type', bond_k_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('bond_r0_type', bond_r0_type, [mstype.float32], self.name)
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return bond_r0_type, bond_r0_type
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class DihedralForce(PrimitiveWithInfer):
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"""
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DihedralForce:
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@ -259,18 +351,18 @@ class DihedralForce(PrimitiveWithInfer):
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Inputs:
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- **uint_crd_f** (Tensor, uint32) - [N, 3], the unsigned int coordinates
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value of each atom.
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- **scalar_f** (Tensor, float32) - [3, 1], the 3-D scale factor between
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- **scalar_f** (Tensor, float32) - [3, ], the 3-D scale factor between
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the real space float coordinates and the unsigned int coordinates.
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- **atom_a** (Tensor, int32) - [M, 1], the 1st atom index of each dihedral.
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- **atom_b** (Tensor, int32) - [M, 1], the 2nd atom index of each dihedral.
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- **atom_c** (Tensor, int32) - [M, 1], the 3rd atom index of each dihedral.
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- **atom_d** (Tensor, int32) - [M, 1], the 4th atom index of each dihedral.
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- **atom_a** (Tensor, int32) - [M, ], the 1st atom index of each dihedral.
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- **atom_b** (Tensor, int32) - [M, ], the 2nd atom index of each dihedral.
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- **atom_c** (Tensor, int32) - [M, ], the 3rd atom index of each dihedral.
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- **atom_d** (Tensor, int32) - [M, ], the 4th atom index of each dihedral.
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4 atoms are connected in the form a-b-c-d.
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- **ipn** (Tensor, int32) - [M, 1], the period of dihedral angle of each dihedral.
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- **pk** (Tensor, float32) - [M, 1], the force constant of each dihedral.
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- **gamc** (Tensor, float32) - [M, 1], k*cos(phi_0) of each dihedral.
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- **gams** (Tensor, float32) - [M, 1], k*sin(phi_0) of each dihedral.
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- **pn** (Tensor, float32) - [M, 1], the floating point form of ipn.
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- **ipn** (Tensor, int32) - [M, ], the period of dihedral angle of each dihedral.
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- **pk** (Tensor, float32) - [M, ], the force constant of each dihedral.
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- **gamc** (Tensor, float32) - [M, ], k*cos(phi_0) of each dihedral.
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- **gams** (Tensor, float32) - [M, ], k*sin(phi_0) of each dihedral.
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- **pn** (Tensor, float32) - [M, ], the floating point form of ipn.
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Outputs:
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- **frc_f** (Tensor, float32) - [N, 3], the force felt by each atom.
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@ -289,6 +381,29 @@ class DihedralForce(PrimitiveWithInfer):
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outputs=['frc_f'])
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self.add_prim_attr('dihedral_numbers', self.dihedral_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
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ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
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cls_name = self.name
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
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validator.check_int(
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atom_d_shape[0], M, Rel.EQ, "atom_d_shape", cls_name)
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validator.check_int(ipn_shape[0], M, Rel.EQ, "ipn_shape", cls_name)
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validator.check_int(pk_shape[0], M, Rel.EQ, "pk_shape", cls_name)
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validator.check_int(gamc_shape[0], M, Rel.EQ, "gamc_shape", cls_name)
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validator.check_int(gams_shape[0], M, Rel.EQ, "gams_shape", cls_name)
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validator.check_int(pn_shape[0], M, Rel.EQ, "pn_shape", cls_name)
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return uint_crd_f_shape
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, atom_d_type,
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ipn_type, pk_type, gamc_type, gams_type, pn_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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@ -302,7 +417,6 @@ class DihedralForce(PrimitiveWithInfer):
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validator.check_tensor_dtype_valid('gamc_type', gamc_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('gams_type', gams_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('pn_type', pn_type, [mstype.float32], self.name)
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return pn_type
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@ -321,7 +435,7 @@ class DihedralEnergy(PrimitiveWithInfer):
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Same as operator DihedralForce().
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Outputs:
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- **ene** (Tensor, float32) - [M, 1], the potential energy for each
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- **ene** (Tensor, float32) - [M, ], the potential energy for each
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dihedral term.
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Supported Platforms:
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@ -338,6 +452,29 @@ class DihedralEnergy(PrimitiveWithInfer):
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outputs=['ene'])
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self.add_prim_attr('dihedral_numbers', self.dihedral_numbers)
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def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
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ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
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cls_name = self.name
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M = atom_a_shape[0]
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validator.check_int(
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uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
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validator.check_int(
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scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
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validator.check_int(
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atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
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validator.check_int(
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atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
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validator.check_int(
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atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
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validator.check_int(
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atom_d_shape[0], M, Rel.EQ, "atom_d_shape", cls_name)
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validator.check_int(ipn_shape[0], M, Rel.EQ, "ipn_shape", cls_name)
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validator.check_int(pk_shape[0], M, Rel.EQ, "pk_shape", cls_name)
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validator.check_int(gamc_shape[0], M, Rel.EQ, "gamc_shape", cls_name)
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validator.check_int(gams_shape[0], M, Rel.EQ, "gams_shape", cls_name)
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validator.check_int(pn_shape[0], M, Rel.EQ, "pn_shape", cls_name)
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return [M,]
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def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, atom_d_type,
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ipn_type, pk_type, gamc_type, gams_type, pn_type):
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validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
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@ -351,7 +488,6 @@ class DihedralEnergy(PrimitiveWithInfer):
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validator.check_tensor_dtype_valid('gamc_type', gamc_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('gams_type', gams_type, [mstype.float32], self.name)
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validator.check_tensor_dtype_valid('pn_type', pn_type, [mstype.float32], self.name)
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return pn_type
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@ -368,7 +504,7 @@ class DihedralAtomEnergy(PrimitiveWithInfer):
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Same as operator DihedralEnergy().
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Outputs:
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- **ene** (Tensor, float32) - [N, 1], the accumulated potential
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- **ene** (Tensor, float32) - [N, ], the accumulated potential
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energy for each atom.
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Supported Platforms:
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@ -385,6 +521,30 @@ class DihedralAtomEnergy(PrimitiveWithInfer):
|
|||
outputs=['ene'])
|
||||
self.add_prim_attr('dihedral_numbers', self.dihedral_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
|
||||
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
|
||||
cls_name = self.name
|
||||
N = uint_crd_f_shape[0]
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_d_shape[0], M, Rel.EQ, "atom_d_shape", cls_name)
|
||||
validator.check_int(ipn_shape[0], M, Rel.EQ, "ipn_shape", cls_name)
|
||||
validator.check_int(pk_shape[0], M, Rel.EQ, "pk_shape", cls_name)
|
||||
validator.check_int(gamc_shape[0], M, Rel.EQ, "gamc_shape", cls_name)
|
||||
validator.check_int(gams_shape[0], M, Rel.EQ, "gams_shape", cls_name)
|
||||
validator.check_int(pn_shape[0], M, Rel.EQ, "pn_shape", cls_name)
|
||||
return [N,]
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, atom_d_type,
|
||||
ipn_type, pk_type, gamc_type, gams_type, pn_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
@ -398,7 +558,6 @@ class DihedralAtomEnergy(PrimitiveWithInfer):
|
|||
validator.check_tensor_dtype_valid('gamc_type', gamc_type, [mstype.float32], self.name)
|
||||
validator.check_tensor_dtype_valid('gams_type', gams_type, [mstype.float32], self.name)
|
||||
validator.check_tensor_dtype_valid('pn_type', pn_type, [mstype.float32], self.name)
|
||||
|
||||
return pn_type
|
||||
|
||||
|
||||
|
|
@ -415,7 +574,7 @@ class DihedralForceWithAtomEnergy(PrimitiveWithInfer):
|
|||
|
||||
Outputs:
|
||||
- **frc_f** (Tensor, float32) - [N, 3], same as operator DihedralForce().
|
||||
- **ene** (Tensor, float32) - [N, 1], same as operator DihedralAtomEnergy().
|
||||
- **ene** (Tensor, float32) - [N, ], same as operator DihedralAtomEnergy().
|
||||
|
||||
Supported Platforms:
|
||||
``GPU``
|
||||
|
|
@ -431,6 +590,30 @@ class DihedralForceWithAtomEnergy(PrimitiveWithInfer):
|
|||
outputs=['frc_f', 'ene'])
|
||||
self.add_prim_attr('dihedral_numbers', self.dihedral_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
|
||||
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
|
||||
cls_name = self.name
|
||||
N = uint_crd_f_shape[0]
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_d_shape[0], M, Rel.EQ, "atom_d_shape", cls_name)
|
||||
validator.check_int(ipn_shape[0], M, Rel.EQ, "ipn_shape", cls_name)
|
||||
validator.check_int(pk_shape[0], M, Rel.EQ, "pk_shape", cls_name)
|
||||
validator.check_int(gamc_shape[0], M, Rel.EQ, "gamc_shape", cls_name)
|
||||
validator.check_int(gams_shape[0], M, Rel.EQ, "gams_shape", cls_name)
|
||||
validator.check_int(pn_shape[0], M, Rel.EQ, "pn_shape", cls_name)
|
||||
return uint_crd_f_shape, [N,]
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, atom_d_type,
|
||||
ipn_type, pk_type, gamc_type, gams_type, pn_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
@ -444,7 +627,6 @@ class DihedralForceWithAtomEnergy(PrimitiveWithInfer):
|
|||
validator.check_tensor_dtype_valid('gamc_type', gamc_type, [mstype.float32], self.name)
|
||||
validator.check_tensor_dtype_valid('gams_type', gams_type, [mstype.float32], self.name)
|
||||
validator.check_tensor_dtype_valid('pn_type', pn_type, [mstype.float32], self.name)
|
||||
|
||||
return pn_type, pn_type
|
||||
|
||||
|
||||
|
|
@ -470,14 +652,14 @@ class AngleForce(PrimitiveWithInfer):
|
|||
Inputs:
|
||||
- **uint_crd_f** (Tensor, uint32) - [N, 3], the unsigned int coordinate
|
||||
value of each atom.
|
||||
- **scaler_f** (Tensor, float32) - [3, 1], the 3-D scale factor between
|
||||
- **scaler_f** (Tensor, float32) - [3, ], the 3-D scale factor between
|
||||
the real space float coordinates and the unsigned int coordinates.
|
||||
- **atom_a** (Tensor, int32) - [M, 1], the 1st atom index of each angle.
|
||||
- **atom_b** (Tensor, int32) - [M, 1], the 2nd and the central atom index
|
||||
- **atom_a** (Tensor, int32) - [M, ], the 1st atom index of each angle.
|
||||
- **atom_b** (Tensor, int32) - [M, ], the 2nd and the central atom index
|
||||
of each angle.
|
||||
- **atom_c** (Tensor, int32) - [M, 1], the 3rd atom index of each angle.
|
||||
- **angle_k** (Tensor, float32) - [M, 1], the force constant for each angle.
|
||||
- **angle_theta0** (Tensor, float32) - [M, 1], the equilibrium position value
|
||||
- **atom_c** (Tensor, int32) - [M, ], the 3rd atom index of each angle.
|
||||
- **angle_k** (Tensor, float32) - [M, ], the force constant for each angle.
|
||||
- **angle_theta0** (Tensor, float32) - [M, ], the equilibrium position value
|
||||
for each angle.
|
||||
|
||||
Outputs:
|
||||
|
|
@ -497,6 +679,26 @@ class AngleForce(PrimitiveWithInfer):
|
|||
outputs=['frc_f'])
|
||||
self.add_prim_attr('angle_numbers', self.angle_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
|
||||
angle_theta0_shape):
|
||||
cls_name = self.name
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_k_shape[0], M, Rel.EQ, "angle_k_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_theta0_shape[0], M, Rel.EQ, "angle_theta0_shape", cls_name)
|
||||
return uint_crd_f_shape
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, angle_k_type,
|
||||
angle_theta0_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
@ -526,7 +728,7 @@ class AngleEnergy(PrimitiveWithInfer):
|
|||
Same as operator AngleForce().
|
||||
|
||||
Outputs:
|
||||
- **ene** (Tensor, float32) - [M, 1], the potential energy for
|
||||
- **ene** (Tensor, float32) - [M, ], the potential energy for
|
||||
each angle term.
|
||||
|
||||
Supported Platforms:
|
||||
|
|
@ -543,6 +745,26 @@ class AngleEnergy(PrimitiveWithInfer):
|
|||
outputs=['ene'])
|
||||
self.add_prim_attr('angle_numbers', self.angle_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
|
||||
angle_theta0_shape):
|
||||
cls_name = self.name
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_k_shape[0], M, Rel.EQ, "angle_k_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_theta0_shape[0], M, Rel.EQ, "angle_theta0_shape", cls_name)
|
||||
return [M,]
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, angle_k_type,
|
||||
angle_theta0_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
@ -568,7 +790,7 @@ class AngleAtomEnergy(PrimitiveWithInfer):
|
|||
Same as operator AngleForce().
|
||||
|
||||
Outputs:
|
||||
- **ene** (Tensor, float32) - [N, 1], the accumulated potential energy
|
||||
- **ene** (Tensor, float32) - [N, ], the accumulated potential energy
|
||||
for each atom.
|
||||
|
||||
Supported Platforms:
|
||||
|
|
@ -585,6 +807,27 @@ class AngleAtomEnergy(PrimitiveWithInfer):
|
|||
outputs=['ene'])
|
||||
self.add_prim_attr('angle_numbers', self.angle_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
|
||||
angle_theta0_shape):
|
||||
cls_name = self.name
|
||||
N = uint_crd_f_shape[0]
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_k_shape[0], M, Rel.EQ, "angle_k_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_theta0_shape[0], M, Rel.EQ, "angle_theta0_shape", cls_name)
|
||||
return [N,]
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, angle_k_type,
|
||||
angle_theta0_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
@ -610,7 +853,7 @@ class AngleForceWithAtomEnergy(PrimitiveWithInfer):
|
|||
|
||||
Outputs:
|
||||
- **frc_f** (Tensor, float32) - [N, 3], same as operator AngleForce().
|
||||
- **ene** (Tensor, float) - [N, 1], same as operator AngleAtomEnergy().
|
||||
- **ene** (Tensor, float) - [N, ], same as operator AngleAtomEnergy().
|
||||
|
||||
Supported Platforms:
|
||||
``GPU``
|
||||
|
|
@ -626,6 +869,27 @@ class AngleForceWithAtomEnergy(PrimitiveWithInfer):
|
|||
outputs=['frc_f', 'ene'])
|
||||
self.add_prim_attr('angle_numbers', self.angle_numbers)
|
||||
|
||||
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
|
||||
angle_theta0_shape):
|
||||
cls_name = self.name
|
||||
N = uint_crd_f_shape[0]
|
||||
M = atom_a_shape[0]
|
||||
validator.check_int(
|
||||
uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
scaler_f_shape[0], 3, Rel.EQ, "scaler_f_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_a_shape[0], M, Rel.EQ, "atom_a_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_b_shape[0], M, Rel.EQ, "atom_b_shape", cls_name)
|
||||
validator.check_int(
|
||||
atom_c_shape[0], M, Rel.EQ, "atom_c_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_k_shape[0], M, Rel.EQ, "angle_k_shape", cls_name)
|
||||
validator.check_int(
|
||||
angle_theta0_shape[0], M, Rel.EQ, "angle_theta0_shape", cls_name)
|
||||
return uint_crd_f_shape, [N,]
|
||||
|
||||
def infer_dtype(self, uint_crd_f_dtype, scaler_f_type, atom_a_type, atom_b_type, atom_c_type, angle_k_type,
|
||||
angle_theta0_type):
|
||||
validator.check_tensor_dtype_valid('uint_crd_f_dtype', uint_crd_f_dtype, [mstype.uint32], self.name)
|
||||
|
|
|
|||
Loading…
Reference in New Issue