Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

added relu_ to torch frontend and tested #6033

Closed
wants to merge 2 commits into from
Closed

added relu_ to torch frontend and tested #6033

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
d0a3775
Update non_linear_activation_functions.py
TAUIL-Abd-Elilah Oct 22, 2022
a2e27a0
Update test_non_linear_activation_functions.py
TAUIL-Abd-Elilah Oct 22, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions ivy/functional/frontends/torch/nn/functional/non_linear_activation_functions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,6 +49,12 @@ def _selu_with_inplace(input, inplace=False):
return ret


def relu_(input):
ret = ivy.maximum(0, input)
ivy.inplace_update(input, ret)
return input


def _rrelu(input, lower=1.0 / 8, upper=1.0 / 3, training=False, inplace=False):
if training:
# alpha = ivy.random_uniform(low=lower, high=upper)
Expand Down
34 changes: 34 additions & 0 deletions ivy_tests/test_ivy/test_frontends/test_torch/test_non_linear_activation_functions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,40 @@ def test_torch_softmax(
)


# relu_
@handle_cmd_line_args
@given(
dtype_and_input=helpers.dtype_and_values(
available_dtypes=helpers.get_dtypes("numeric"),
),
num_positional_args=helpers.num_positional_args(
fn_name="ivy.functional.frontends.torch.relu_"
),
with_inplace=st.booleans(),
)
def test_torch_relu_(
dtype_and_input,
with_inplace,
as_variable,
num_positional_args,
native_array,
):
input_dtype, input = dtype_and_input
_filter_dtypes(input_dtype)
helpers.test_frontend_function(
input_dtypes=input_dtype,
as_variable_flags=as_variable,
with_out=False,
with_inplace=with_inplace,
num_positional_args=num_positional_args,
native_array_flags=native_array,
frontend="torch",
fn_tree="nn.functional.relu_",
test_values=False,
input=input[0],
)


# gelu
@handle_cmd_line_args
@given(
Expand Down