Lines Matching full:rand

54         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
55         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
56         mbuff = torch.rand(10, requires_grad=True, dtype=torch.float64)
72         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
73         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
77         state["exp_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
78         state["exp_avg_sq"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
79         state["max_exp_avg_sq"] = torch.rand(
97         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
98         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
100         state["square_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
101         state["momentum_buffer"] = torch.rand(
105         state["grad_avg"] = 1e-2 * torch.rand(
129         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
130         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
134         state["square_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
135         state["acc_delta"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
150         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
151         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
155         state["sum"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
170         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
171         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
175         state["exp_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
176         state["exp_inf"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
195         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
196         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
202         state["ax"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
218         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
219         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
223         state["prev"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
224         state["step_size"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
240         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
241         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
245         state["exp_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
246         state["exp_avg_sq"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
247         state["max_exp_avg_sq"] = torch.rand(
265         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
266         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
270         state["exp_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
271         state["exp_avg_sq"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
300         p = torch.rand(10, requires_grad=True, dtype=torch.float64)
301         grad = torch.rand(10, requires_grad=True, dtype=torch.float64)
305         state["exp_avg"] = torch.rand(10, requires_grad=True, dtype=torch.float64)
306         state["exp_avg_sq"] = torch.rand(10, requires_grad=True, dtype=torch.float64)