fix optimizer args as same dtype on GPU

mindnlp/core/ops/optim.py

@@ -1,19 +1,38 @@
 """optim op"""
+import mindspore
 from mindspore import ops
 from mindspore.ops._primitive_cache import _get_cache_prim
 
+DEVICE_TARGET = mindspore.get_context('device_target')
+
 _adadelta = ops.ApplyAdadelta()
 def raw_adadelta(param, square_avg, acc_delta, lr, rho, eps, grad):
     return _adadelta(param, square_avg, acc_delta, lr, rho, eps, grad)
 
 _adam = ops.Adam()
 def raw_adam(param, exp_avg, exp_avg_sq, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad):
     # var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad
+    if DEVICE_TARGET == 'GPU' and param.dtype != mindspore.float32:
+        beta1_power, beta2_power, lr, beta1, beta2, epsilon = mindspore.tensor(beta1_power, dtype=param.dtype), \
+                                                            mindspore.tensor(beta2_power, dtype=param.dtype), \
+                                                            mindspore.tensor(lr, dtype=param.dtype), \
+                                                            mindspore.tensor(beta1, dtype=param.dtype), \
+                                                            mindspore.tensor(beta2, dtype=param.dtype), \
+                                                            mindspore.tensor(epsilon, dtype=param.dtype)
     return _adam(param, exp_avg, exp_avg_sq, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad)
 
 _adam_amsgrad = ops.ApplyAdamWithAmsgradV2()
 def raw_adam_amsgrad(param, exp_avg, exp_avg_sq, max_exp_avg_sq, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad):
     # var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad
+
+    if DEVICE_TARGET == 'GPU' and param.dtype != mindspore.float32:
+        beta1_power, beta2_power, lr, beta1, beta2, epsilon = mindspore.tensor(beta1_power, dtype=param.dtype), \
+                                                            mindspore.tensor(beta2_power, dtype=param.dtype), \
+                                                            mindspore.tensor(lr, dtype=param.dtype), \
+                                                            mindspore.tensor(beta1, dtype=param.dtype), \
+                                                            mindspore.tensor(beta2, dtype=param.dtype), \
+                                                            mindspore.tensor(epsilon, dtype=param.dtype)
+
     return _adam_amsgrad(param, exp_avg, exp_avg_sq, max_exp_avg_sq,
                          beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad)