diff --git a/tests/sweep_framework/sweeps/eltwise/unary/log10/log10.py b/tests/sweep_framework/sweeps/eltwise/unary/log10/log10.py
index dcf002572652..87b8be53ade0 100644
--- a/tests/sweep_framework/sweeps/eltwise/unary/log10/log10.py
+++ b/tests/sweep_framework/sweeps/eltwise/unary/log10/log10.py
@@ -29,13 +29,22 @@
         + gen_shapes([1, 32, 32], [12, 256, 256], [1, 32, 32], 16)
         + gen_shapes([32, 32], [256, 256], [32, 32], 32),
         "input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
-        "input_a_layout": [ttnn.TILE_LAYOUT],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
         "output_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }
 
 
+# Invalidate vector is called during the generation phase where each vector will be passed in.
+# If invalidated, the vector will still be stored but will be skipped.
+# Returns False, None if the vector is valid, and True, str with a reason for invalidation if it is invalid.
+def invalidate_vector(test_vector) -> Tuple[bool, Optional[str]]:
+    if test_vector["input_a_layout"] == ttnn.ROW_MAJOR_LAYOUT:
+        return True, "Row Major layout is not supported"
+    return False, None
+
+
 # This is the run instructions for the test, defined by the developer.
 # The run function must take the above-defined parameters as inputs.
 # The runner will call this run function with each test vector, and the returned results from this function will be stored.
diff --git a/tests/sweep_framework/sweeps/eltwise/unary/log1p/log1p.py b/tests/sweep_framework/sweeps/eltwise/unary/log1p/log1p.py
index b29fb634f32f..4dbe8e0e5144 100644
--- a/tests/sweep_framework/sweeps/eltwise/unary/log1p/log1p.py
+++ b/tests/sweep_framework/sweeps/eltwise/unary/log1p/log1p.py
@@ -29,13 +29,22 @@
         + gen_shapes([1, 32, 32], [12, 256, 256], [1, 32, 32], 16)
         + gen_shapes([32, 32], [256, 256], [32, 32], 32),
         "input_a_dtype": [ttnn.bfloat16],
-        "input_a_layout": [ttnn.TILE_LAYOUT],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
         "output_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }
 
 
+# Invalidate vector is called during the generation phase where each vector will be passed in.
+# If invalidated, the vector will still be stored but will be skipped.
+# Returns False, None if the vector is valid, and True, str with a reason for invalidation if it is invalid.
+def invalidate_vector(test_vector) -> Tuple[bool, Optional[str]]:
+    if test_vector["input_a_layout"] == ttnn.ROW_MAJOR_LAYOUT:
+        return True, "Row Major layout is not supported"
+    return False, None
+
+
 # This is the run instructions for the test, defined by the developer.
 # The run function must take the above-defined parameters as inputs.
 # The runner will call this run function with each test vector, and the returned results from this function will be stored.
diff --git a/tests/sweep_framework/sweeps/eltwise/unary/log2/log2.py b/tests/sweep_framework/sweeps/eltwise/unary/log2/log2.py
index 47d8cb2daadd..ab7116f8b8f1 100644
--- a/tests/sweep_framework/sweeps/eltwise/unary/log2/log2.py
+++ b/tests/sweep_framework/sweeps/eltwise/unary/log2/log2.py
@@ -29,13 +29,22 @@
         + gen_shapes([1, 32, 32], [12, 256, 256], [1, 32, 32], 16)
         + gen_shapes([32, 32], [256, 256], [32, 32], 32),
         "input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
-        "input_a_layout": [ttnn.TILE_LAYOUT],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
         "output_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }
 
 
+# Invalidate vector is called during the generation phase where each vector will be passed in.
+# If invalidated, the vector will still be stored but will be skipped.
+# Returns False, None if the vector is valid, and True, str with a reason for invalidation if it is invalid.
+def invalidate_vector(test_vector) -> Tuple[bool, Optional[str]]:
+    if test_vector["input_a_layout"] == ttnn.ROW_MAJOR_LAYOUT:
+        return True, "Row Major layout is not supported"
+    return False, None
+
+
 # This is the run instructions for the test, defined by the developer.
 # The run function must take the above-defined parameters as inputs.
 # The runner will call this run function with each test vector, and the returned results from this function will be stored.
diff --git a/tests/sweep_framework/sweeps/eltwise/unary/log_sigmoid/log_sigmoid.py b/tests/sweep_framework/sweeps/eltwise/unary/log_sigmoid/log_sigmoid.py
index e783f8dd12d9..a0e8601c053a 100644
--- a/tests/sweep_framework/sweeps/eltwise/unary/log_sigmoid/log_sigmoid.py
+++ b/tests/sweep_framework/sweeps/eltwise/unary/log_sigmoid/log_sigmoid.py
@@ -29,13 +29,22 @@
         + gen_shapes([1, 32, 32], [12, 256, 256], [1, 32, 32], 16)
         + gen_shapes([32, 32], [256, 256], [32, 32], 32),
         "input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
-        "input_a_layout": [ttnn.TILE_LAYOUT],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
         "output_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }
 
 
+# Invalidate vector is called during the generation phase where each vector will be passed in.
+# If invalidated, the vector will still be stored but will be skipped.
+# Returns False, None if the vector is valid, and True, str with a reason for invalidation if it is invalid.
+def invalidate_vector(test_vector) -> Tuple[bool, Optional[str]]:
+    if test_vector["input_a_layout"] == ttnn.ROW_MAJOR_LAYOUT:
+        return True, "Row Major layout is not supported"
+    return False, None
+
+
 # This is the run instructions for the test, defined by the developer.
 # The run function must take the above-defined parameters as inputs.
 # The runner will call this run function with each test vector, and the returned results from this function will be stored.