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Adding isfinite and isinf torch frontend #3752

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Aug 30, 2022
Merged

Adding isfinite and isinf torch frontend #3752

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8 changes: 8 additions & 0 deletions ivy/functional/frontends/torch/comparison_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,3 +97,11 @@ def isclose(input, other, rtol=1e-05, atol=1e-08, equal_nan=False):


isclose.unsupported_dtypes = ("float16",)


def isfinite(input):
return ivy.isfinite(input)


def isinf(input):
return ivy.isinf(input)
72 changes: 72 additions & 0 deletions ivy_tests/test_ivy/test_frontends/test_torch/test_comparison_ops.py
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Expand Up @@ -300,3 +300,75 @@ def test_torch_isclose(
atol=1e-08,
equal_nan=equal_nan,
)


# isifinite
@handle_cmd_line_args
@given(
dtype_and_input=helpers.dtype_and_values(
available_dtypes=tuple(
set(ivy_np.valid_numeric_dtypes).intersection(
set(ivy_torch.valid_numeric_dtypes)
),
),
allow_inf=True,
),
num_positional_args=helpers.num_positional_args(
fn_name="ivy.functional.frontends.torch.isfinite"
),
)
def test_torch_isfinite(
dtype_and_input,
as_variable,
num_positional_args,
native_array,
fw,
):
input_dtype, input = dtype_and_input
helpers.test_frontend_function(
input_dtypes=input_dtype,
as_variable_flags=as_variable,
with_out=False,
num_positional_args=num_positional_args,
native_array_flags=native_array,
fw=fw,
frontend="torch",
fn_tree="isfinite",
input=np.asarray(input, dtype=input_dtype),
)


# isinf
@handle_cmd_line_args
@given(
dtype_and_input=helpers.dtype_and_values(
available_dtypes=tuple(
set(ivy_np.valid_numeric_dtypes).intersection(
set(ivy_torch.valid_numeric_dtypes)
),
),
allow_inf=True,
),
num_positional_args=helpers.num_positional_args(
fn_name="ivy.functional.frontends.torch.isinf"
),
)
def test_torch_isinf(
dtype_and_input,
as_variable,
num_positional_args,
native_array,
fw,
):
input_dtype, input = dtype_and_input
helpers.test_frontend_function(
input_dtypes=input_dtype,
as_variable_flags=as_variable,
with_out=False,
num_positional_args=num_positional_args,
native_array_flags=native_array,
fw=fw,
frontend="torch",
fn_tree="isinf",
input=np.asarray(input, dtype=input_dtype),
)