remove useless platform args and comment

colossalai/kernel/cpu_adam_loader.py

@@ -12,37 +12,6 @@ class CPUAdamLoader(BaseKernelLoader):
     Usage:
         # init
         cpu_adam = CPUAdamLoader().load()
-        cpu_adam_op = cpu_adam.CPUAdamOptimizer(
-            alpha, beta1, beta2, epsilon, weight_decay, adamw_mode,
-        )
-        ...
-        # optim step
-        cpu_adam_op.step(
-            step, lr, beta1, beta2, epsilon, weight_decay, bias_correction,
-            params, grads, exp_avg, exp_avg_sq, loss_scale,
-        )
-
-    Args:
-        func CPUAdamOptimizer:
-            alpha (float): learning rate. Default to 1e-3.
-            beta1 (float): coefficients used for computing running averages of gradient. Default to 0.9.
-            beta2 (float): coefficients used for computing running averages of its square. Default to 0.99.
-            epsilon (float): term added to the denominator to improve numerical stability. Default to 1e-8.
-            weight_decay (float): weight decay (L2 penalty). Default to 0.
-            adamw_mode (bool): whether to use the adamw. Default to True.
-        func step:
-            step (int): current step.
-            lr (float): learning rate.
-            beta1 (float): coefficients used for computing running averages of gradient.
-            beta2 (float): coefficients used for computing running averages of its square.
-            epsilon (float): term added to the denominator to improve numerical stability.
-            weight_decay (float): weight decay (L2 penalty).
-            bias_correction (bool): whether to use bias correction.
-            params (torch.Tensor): parameter.
-            grads (torch.Tensor): gradient.
-            exp_avg (torch.Tensor): exp average.
-            exp_avg_sq (torch.Tensor): exp average square.
-            loss_scale (float): loss scale value.
     """
 
     def __init__(self):
@@ -57,7 +26,7 @@ class CPUAdamLoader(BaseKernelLoader):
     def fetch_kernel(self):
         if platform.machine() == "x86_64":
             kernel = self._extension_map["x86"]().fetch()
-        elif platform.machine() in ["aarch64", "aarch64_be", "armv8b", "armv8l"]:
+        elif platform.machine() == "aarch64":
             kernel = self._extension_map["arm"]().fetch()
         else:
             raise Exception("not supported")