Fixes pytorch#136559
As we upgrade to NumPy 2, torch falsely filtered out `numpy.random` as unsupported in dynamo tracking.
This PR changes the filtering rules to include them while keeping behavior with numpy 1 unchanged.

Before this PR, the following tests failed:

```
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/dynamo/test_functions.py -k FunctionTests.test_numpy_random
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/dynamo/test_unspec.py -k UnspecTests.test_to_tensor
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/test_fake_tensor.py -k FakeTensorTest.test_export_numpy
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/test_fake_tensor.py -k PropagateRealTensorsFakeTensorTest.test_export_numpy_propagate_real_tensors
```

With this PR, the supported/unsupported ops in NumPy 1 are not changed.
For NumPy 2, only the `numpy.random` ops that are already supported with NumPy 1 are added to the supported list.

I used the following scripts to check the differences before and after the change for both NumPy 1 & 2.
The output is empty for NumPy 1 since there is no change.
The output is a list of `numpy.random` that considered supported for NumPy 2.

```py
from torch._dynamo import trace_rules
import numpy as np

def new_numpy_function_ids():
    unsupported_funcs = {"seed", "ranf", "get_bit_generator", "RandomState", "set_bit_generator", "sample"}

    def is_supported(k, v, mod):
        if not callable(v):
            return False
        if not getattr(v, "__module__", None):
            return True
        if v.__module__ == mod.__name__:
            return True
        if v.__module__ == "numpy.random.mtrand" and mod.__name__== "numpy.random" and k not in unsupported_funcs:
            return True
        return False
    rv = {}
    for mod in trace_rules.NP_SUPPORTED_MODULES:
        for k, v in mod.__dict__.items():
            if is_supported(k, v, mod):
                rv[id(v)] = f"{mod.__name__}.{k}"
    return rv

def old_numpy_function_ids():
    rv = {}
    for mod in trace_rules.NP_SUPPORTED_MODULES:
        rv.update(
            {
                id(v): f"{mod.__name__}.{k}"
                for k, v in mod.__dict__.items()
                if callable(v)
                and (getattr(v, "__module__", None) or mod.__name__) == mod.__name__
            }
        )
    return rv

rv1 = set(old_numpy_function_ids().values())
rv2 = set(new_numpy_function_ids().values())

for v in (rv1 - rv2):
    print(v)
print("****")
for v in (rv2 - rv1):
    print(v)
```

Pull Request resolved: pytorch#138686
Approved by: https://github.com/lezcano, https://github.com/williamwen42

This reverts commit 124eac2.

Reverted pytorch#138686 on behalf of https://github.com/huydhn due to Sorry for reverting your change, but I am seeing inductor failure with hf_BigBird number of graph breaks after it lands ([comment](pytorch#138686 (comment)))

Fixes pytorch#136559
As we upgrade to NumPy 2, torch falsely filtered out `numpy.random` as unsupported in dynamo tracking.
This PR changes the filtering rules to include them while keeping behavior with numpy 1 unchanged.

Before this PR, the following tests failed:

```
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/dynamo/test_functions.py -k FunctionTests.test_numpy_random
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/dynamo/test_unspec.py -k UnspecTests.test_to_tensor
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/test_fake_tensor.py -k FakeTensorTest.test_export_numpy
PYTORCH_TEST_WITH_ASAN=1 PYTORCH_TEST_WITH_UBSAN=1 python test/test_fake_tensor.py -k PropagateRealTensorsFakeTensorTest.test_export_numpy_propagate_real_tensors
```

With this PR, the supported/unsupported ops in NumPy 1 are not changed.
For NumPy 2, only the `numpy.random` ops that are already supported with NumPy 1 are added to the supported list.

I used the following scripts to check the differences before and after the change for both NumPy 1 & 2.
The output is empty for NumPy 1 since there is no change.
The output is a list of `numpy.random` that considered supported for NumPy 2.

```py
from torch._dynamo import trace_rules
import numpy as np

def new_numpy_function_ids():
    unsupported_funcs = {"seed", "ranf", "get_bit_generator", "RandomState", "set_bit_generator", "sample"}

    def is_supported(k, v, mod):
        if not callable(v):
            return False
        if not getattr(v, "__module__", None):
            return True
        if v.__module__ == mod.__name__:
            return True
        if v.__module__ == "numpy.random.mtrand" and mod.__name__== "numpy.random" and k not in unsupported_funcs:
            return True
        return False
    rv = {}
    for mod in trace_rules.NP_SUPPORTED_MODULES:
        for k, v in mod.__dict__.items():
            if is_supported(k, v, mod):
                rv[id(v)] = f"{mod.__name__}.{k}"
    return rv

def old_numpy_function_ids():
    rv = {}
    for mod in trace_rules.NP_SUPPORTED_MODULES:
        rv.update(
            {
                id(v): f"{mod.__name__}.{k}"
                for k, v in mod.__dict__.items()
                if callable(v)
                and (getattr(v, "__module__", None) or mod.__name__) == mod.__name__
            }
        )
    return rv

rv1 = set(old_numpy_function_ids().values())
rv2 = set(new_numpy_function_ids().values())

for v in (rv1 - rv2):
    print(v)
print("****")
for v in (rv2 - rv1):
    print(v)
```

Pull Request resolved: pytorch#138686
Approved by: https://github.com/williamwen42