#16066: refactor

tests/ttnn/unit_tests/operations/test_bernoulli.py

@@ -94,7 +94,7 @@ def test_bernoulli(shape, seed, in_dtype, out_dtype, device, is_out_alloc):
 @pytest.mark.parametrize("out_dtype", ["float32"])
 @pytest.mark.parametrize("is_out_alloc", [True, False])
 def test_bernoulli_callback(shape, seed, in_dtype, out_dtype, device, is_out_alloc, use_program_cache):
-    torch.manual_seed(0)
+    torch.manual_seed(seed)
     num_program_cache_entries_list = []
     for _ in range(2):
         run_bernoulli(shape, in_dtype, out_dtype, device, seed=seed, is_out_alloc=is_out_alloc)

tests/ttnn/unit_tests/operations/test_uniform.py

@@ -95,7 +95,6 @@ def run_uniform(shape, rand_range, dtype, device, seed=0, compute_kernel_options
         )
 
 
-@pytest.mark.skip("#16066: Undefined behaviour. It will fail on some runs and pass on others since it's stochastic.")
 @skip_for_grayskull("Requires wormhole_b0 to run")
 @pytest.mark.parametrize(
     "shape",
@@ -111,7 +110,6 @@ def run_uniform(shape, rand_range, dtype, device, seed=0, compute_kernel_options
 @pytest.mark.parametrize("dtype", ["bfloat16", "float32"])
 @pytest.mark.parametrize("seed", [2024, 19, 522021])
 def test_uniform(shape, rand_range, dtype, seed, device):
-    # for _ in range(200):
     torch.manual_seed(seed)
     run_uniform(shape, rand_range, dtype, device, seed=seed)
 

ttnn/cpp/ttnn/operations/uniform/uniform.cpp

@@ -4,7 +4,6 @@
 // SPDX-License-Identifier: Apache-2.0
 
 #include "uniform.hpp"
-#include <cstdint>
 
 #include "device/uniform_device_operation.hpp"
 

ttnn/cpp/ttnn/operations/uniform/uniform.hpp

@@ -5,7 +5,6 @@
 #pragma once
 #include "ttnn/decorators.hpp"
 #include "ttnn/operations/core/compute_kernel/compute_kernel_config.hpp"
-#include <cstdint>
 
 namespace ttnn::operations::uniform {
 struct Uniform {