poisson_nll_loss in pytorch frontend (ivy-llc#10531)

Added poisson_nll_loss to the PyTorch frontend. 

Co-authored-by: Yusha Arif <101613943+YushaArif99@users.noreply.github.com>

ivy/functional/frontends/torch/nn/functional/loss_functions.py

@@ -367,3 +367,29 @@ def margin_ranking_loss(
     loss = ivy.where(loss < 0, 0, loss)
     reduction = _get_reduction(reduction, size_average, reduce)
     return reduction(loss)
+
+
+@to_ivy_arrays_and_back
+@with_unsupported_dtypes({"1.11.0 and below": ("float16", "bfloat16")}, "torch")
+def poisson_nll_loss(
+    input,
+    target,
+    log_input=True,
+    full=False,
+    size_average=None,
+    eps=1e-8,
+    reduce=None,
+    reduction="mean",
+):
+    if log_input:
+        loss = ivy.exp(input) - target * input
+    else:
+        loss = input - target * ivy.log(input + eps)
+    if full:
+        approximation = (
+            target * ivy.log(target) - target + 0.5 * ivy.log(2 * ivy.pi * target)
+        )
+        loss += ivy.where(target > 1, approximation, 0)
+
+    reduction = _get_reduction(reduction, size_average, reduce)
+    return reduction(loss)

ivy_tests/test_ivy/test_frontends/test_torch/test_loss_functions.py

@@ -699,3 +699,60 @@ def test_torch_margin_ranking_loss(
         reduce=reduce,
         reduction=reduction,
     )
+
+
+# poisson_nll_loss
+@handle_frontend_test(
+    fn_tree="torch.nn.functional.poisson_nll_loss",
+    dtype_and_input=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=0.0,
+        max_value=1.0,
+        allow_inf=False,
+        min_num_dims=2,
+        max_num_dims=2,
+        min_dim_size=1,
+    ),
+    dtype_and_target=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        min_value=0,
+        min_num_dims=1,
+        max_num_dims=1,
+        min_dim_size=2,
+    ),
+    log_input=st.booleans(),
+    full=st.booleans(),
+    size_average=st.booleans(),
+    reduce=st.booleans(),
+    reduction=st.sampled_from(["mean", "none", "sum"]),
+)
+def test_torch_poisson_nll_loss(
+    *,
+    dtype_and_input,
+    dtype_and_target,
+    log_input,
+    full,
+    size_average,
+    reduce,
+    reduction,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    inputs_dtype, input = dtype_and_input
+    target_dtype, target = dtype_and_target
+    helpers.test_frontend_function(
+        input_dtypes=inputs_dtype + target_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=input[0],
+        target=target[0],
+        log_input=log_input,
+        full=full,
+        size_average=size_average,
+        reduce=reduce,
+        reduction=reduction,
+    )