From decce5635a519117db3f9266e07cc7bfdf4b6bb7 Mon Sep 17 00:00:00 2001
From: Yusha Arif <101613943+YushaArif99@users.noreply.github.com>
Date: Mon, 5 Feb 2024 16:19:44 +0000
Subject: [PATCH] (feat)(torch frontends): added the frontend functions for
 `torch.Tensor.bernoulli_` and `torch.Tensor.numel`

---
 ivy/functional/frontends/torch/random_sampling.py |  4 ++--
 ivy/functional/frontends/torch/tensor.py          | 15 +++++++++++++--
 2 files changed, 15 insertions(+), 4 deletions(-)

diff --git a/ivy/functional/frontends/torch/random_sampling.py b/ivy/functional/frontends/torch/random_sampling.py
index 77f1c96f49230..88dacdb40b0ee 100644
--- a/ivy/functional/frontends/torch/random_sampling.py
+++ b/ivy/functional/frontends/torch/random_sampling.py
@@ -13,9 +13,9 @@
     "torch",
 )
 @to_ivy_arrays_and_back
-def bernoulli(input, *, generator=None, out=None):
+def bernoulli(input, p, *, generator=None, out=None):
     seed = generator.initial_seed() if generator is not None else None
-    return ivy.bernoulli(input, seed=seed, out=out)
+    return ivy.bernoulli(p, logits=input, seed=seed, out=out)
 
 
 @to_ivy_arrays_and_back
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
index 22195e6f3008d..fbaa3dc37d9c4 100644
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -1201,8 +1201,19 @@ def dot(self, tensor):
         return torch_frontend.dot(self, tensor)
 
     @with_supported_dtypes({"2.1.2 and below": ("float32", "float64")}, "torch")
-    def bernoulli(self, *, generator=None, out=None):
-        return torch_frontend.bernoulli(self._ivy_array, generator=generator, out=out)
+    def bernoulli(self, p, *, generator=None, out=None):
+        return torch_frontend.bernoulli(
+            self._ivy_array, p, generator=generator, out=out
+        )
+
+    @with_supported_dtypes({"2.1.2 and below": ("float32", "float64")}, "torch")
+    def bernoulli_(self, p, *, generator=None, out=None):
+        self.ivy_array = self.bernoulli(p, generator=generator, out=out).ivy_array
+        return self
+
+    def numel(self):
+        shape = self.shape
+        return int(ivy.astype(ivy.prod(shape), ivy.int64))
 
     # Special Methods #
     # -------------------#