`elasticai.creator_plugins.quantized_grads.tests.fxpmodel_loss_optim_test`#

Module Contents#

Classes#

`Test1`
`Test2`

API#

class elasticai.creator_plugins.quantized_grads.tests.fxpmodel_loss_optim_test.Test1[source]#

test_pred(pred: torch.Tensor) → None[source]#

test_loss(loss)[source]#

test_grad_weight(model, loss)[source]#

test_grad_bias(model, loss)[source]#

test_new_weight(model, optimizer_step)[source]#

test_new_bias(model, optimizer_step)[source]#

in_features() → int[source]#

out_features() → int[source]#

model(in_features: int, out_features: int) → torch.nn.Sequential[source]#

input(in_features: int) → torch.Tensor[source]#

pred(model: torch.nn.Sequential, input: torch.Tensor) → torch.Tensor[source]#

output(out_features: int) → torch.Tensor[source]#

loss(output: torch.Tensor, pred: torch.Tensor) → torch.Tensor[source]#

optimizer(model: torch.nn.Sequential, loss: torch.Tensor) → torch.optim.Optimizer[source]#

optimizer_step(optimizer: torch.optim.SGD, loss: torch.Tensor) → None[source]#

class elasticai.creator_plugins.quantized_grads.tests.fxpmodel_loss_optim_test.Test2[source]#

test_pred(pred: torch.Tensor) → None[source]#

test_loss(loss)[source]#

test_grad_weight(model, loss)[source]#

test_grad_bias(model, loss)[source]#

test_new_weight(model, optimizer_step)[source]#

test_new_bias(model, optimizer_step)[source]#

in_features() → int[source]#

out_features() → int[source]#

model(in_features: int, out_features: int) → torch.nn.Sequential[source]#

input(in_features: int) → torch.Tensor[source]#

pred(model: torch.nn.Sequential, input: torch.Tensor) → torch.Tensor[source]#

output(out_features: int) → torch.Tensor[source]#

loss(output: torch.Tensor, pred: torch.Tensor) → torch.Tensor[source]#

optimizer(model: torch.nn.Sequential, loss: torch.Tensor) → torch.optim.Optimizer[source]#

optimizer_step(optimizer: torch.optim.SGD, loss: torch.Tensor) → None[source]#