Issue 1:
When I try a simple scan loop using Jax in 64bit on a Windows 10 machine, I get the following error.

import jax
import jax.numpy as jnp
from jax.config import config
config.update('jax_enable_x64', True)

T = 1.0
init_x = 0.0
init_t = 0.0
dt = T / num_steps
def scan_fun(x, t):
x += dt
t += dt
return x, t
xs = jnp.linspace(init_t, T, num_steps, endpoint=True)
jax.lax.scan(scan_fun, init_x, xs[:, jnp.newaxis])[0]

Crashes with the following error

Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2020.3.3\plugins\python\helpers\pydev\_pydevd_bundle\pydevd_exec2.py", line 3, in Exec
exec(exp, global_vars, local_vars)
File "<string>", line 13, in <module>
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\traceback_util.py", line 139, in reraise_with_filtered_traceback
return fun(*args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 1292, in scan
out = scan_p.bind(*itertools.chain(consts, in_flat),
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 1880, in scan_bind
return core.Primitive.bind(scan_p, *args, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 284, in bind
out = top_trace.process_primitive(self, tracers, params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 622, in process_primitive
return primitive.impl(*tracers, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 1379, in _scan_impl
return _scan_impl_loop(
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 1340, in _scan_impl_loop
_, *outs = while_loop(cond_fun, body_fun, init_val)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\traceback_util.py", line 139, in reraise_with_filtered_traceback
return fun(*args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 284, in while_loop
init_vals, init_avals, body_jaxpr, in_tree, *rest = _create_jaxpr(init_val)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 269, in _create_jaxpr
cond_jaxpr, cond_consts, cond_tree = _initial_style_jaxpr(cond_fun, in_tree, init_avals)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\util.py", line 198, in wrapper
return cached(bool(config.x64_enabled), *args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\util.py", line 191, in cached
return f(*args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 73, in _initial_style_jaxpr
jaxpr, consts, out_tree = _initial_style_open_jaxpr(fun, in_tree, in_avals)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\util.py", line 198, in wrapper
return cached(bool(config.x64_enabled), *args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\util.py", line 191, in cached
return f(*args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 68, in _initial_style_open_jaxpr
jaxpr, _, consts = pe.trace_to_jaxpr_dynamic(wrapped_fun, in_avals)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1190, in trace_to_jaxpr_dynamic
jaxpr, out_avals, consts = trace_to_subjaxpr_dynamic(fun, main, in_avals)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1200, in trace_to_subjaxpr_dynamic
ans = fun.call_wrapped(*in_tracers)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\linear_util.py", line 166, in call_wrapped
ans = self.f(*args, **dict(self.params, **kwargs))
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\control_flow.py", line 1324, in cond_fun
return i < length
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 516, in __lt__
def __lt__(self, other): return self.aval._lt(self, other)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 5256, in deferring_binary_op
return binary_op(self, other)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 466, in fn
return lax_fn(x1, x2)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 407, in lt
return lt_p.bind(x, y)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 284, in bind
out = top_trace.process_primitive(self, tracers, params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1062, in process_primitive
out_avals = primitive.abstract_eval(*avals, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 1994, in standard_abstract_eval
return ShapedArray(shape_rule(*avals, **kwargs), dtype_rule(*avals, **kwargs),
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 2070, in naryop_dtype_rule
_check_same_dtypes(name, False, *aval_dtypes)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 6158, in _check_same_dtypes
raise TypeError(msg.format(name, ", ".join(map(str, types))))
TypeError: lt requires arguments to have the same dtypes, got int64, int32.

Issue 2:
When I try a simple cross product calculation using Jax in 64bit on a Windows 10 machine, I get the following error.

import jax.numpy as jnp
from jax.config import config
config.update('jax_enable_x64', True)

x = jnp.array((1.0,1.0,1.0))
y = jnp.array((0.0,0.0,0.0))
z = jnp.cross(x,y)

Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2020.3.3\plugins\python\helpers\pydev\_pydevd_bundle\pydevd_exec2.py", line 3, in Exec
exec(exp, global_vars, local_vars)
File "<input>", line 1, in <module>
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 3938, in cross
return _cross(a, b, axisa, axisb, axisc)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\traceback_util.py", line 139, in reraise_with_filtered_traceback
return fun(*args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\api.py", line 416, in f_jitted
return cpp_jitted_f(context, *args, **kwargs)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\api.py", line 297, in cache_miss
out_flat = xla.xla_call(
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 1394, in bind
return call_bind(self, fun, *args, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 1385, in call_bind
outs = primitive.process(top_trace, fun, tracers, params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 1397, in process
return trace.process_call(self, fun, tracers, params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 625, in process_call
return primitive.impl(f, *tracers, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\xla.py", line 586, in _xla_call_impl
compiled_fun = _xla_callable(fun, device, backend, name, donated_invars,
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\linear_util.py", line 260, in memoized_fun
ans = call(fun, *args)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\xla.py", line 662, in _xla_callable
jaxpr, out_avals, consts = pe.trace_to_jaxpr_final(fun, abstract_args)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1220, in trace_to_jaxpr_final
jaxpr, out_avals, consts = trace_to_subjaxpr_dynamic(fun, main, in_avals)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1200, in trace_to_subjaxpr_dynamic
ans = fun.call_wrapped(*in_tracers)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\linear_util.py", line 166, in call_wrapped
ans = self.f(*args, **dict(self.params, **kwargs))
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 3922, in _cross
a0 = a[..., 0]
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 552, in __getitem__
def __getitem__(self, idx): return self.aval._getitem(self, idx)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 4384, in _rewriting_take
return _gather(arr, treedef, static_idx, dynamic_idx)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 4391, in _gather
indexer = _index_to_gather(shape(arr), idx) # shared with _scatter_update
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 4571, in _index_to_gather
i = _normalize_index(i, x_shape[x_axis]) if normalize_indices else i
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\numpy\lax_numpy.py", line 4224, in _normalize_index
lax.lt(index, _constant_like(index, 0)),
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 407, in lt
return lt_p.bind(x, y)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\core.py", line 284, in bind
out = top_trace.process_primitive(self, tracers, params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\interpreters\partial_eval.py", line 1062, in process_primitive
out_avals = primitive.abstract_eval(*avals, **params)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 1994, in standard_abstract_eval
return ShapedArray(shape_rule(*avals, **kwargs), dtype_rule(*avals, **kwargs),
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 2070, in naryop_dtype_rule
_check_same_dtypes(name, False, *aval_dtypes)
File "C:\Users\Adam\anaconda3\envs\tensorflow\lib\site-packages\jax\_src\lax\lax.py", line 6158, in _check_same_dtypes
raise TypeError(msg.format(name, ", ".join(map(str, types))))
TypeError: lt requires arguments to have the same dtypes, got int64, int32.