import unittest
import numpy as np
from tinygrad.helpers import getenv, DType, DEBUG
from tinygrad.lazy import Device
from tinygrad.tensor import Tensor, dtypes


def _test_to_np(a:Tensor, np_dtype, target):
  print(a)
  na = a.numpy()
  print(na, na.dtype, a.lazydata.realized)
  assert na.dtype == np_dtype
  np.testing.assert_allclose(na, target)

def _test_op(fxn, target_dtype:DType, target):
  c = fxn()
  if DEBUG >= 2: print(c.numpy())
  assert c.dtype == target_dtype
  np.testing.assert_allclose(c.numpy(), target)

def _test_cast(a:Tensor, target_dtype:DType, target): _test_op(lambda: a.cast(target_dtype), target_dtype, target)
def _test_add(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a+b, target_dtype, target)
def _test_mul(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a*b, target_dtype, target)
def _test_matmul(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a@b, target_dtype, target)
def _test_add_upcast(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a+b, target_dtype, target)
def _test_mul_upcast(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a*b, target_dtype, target)
def _test_matmul_upcast(a:Tensor, b:Tensor, target_dtype:DType, target): _test_op(lambda: a@b, target_dtype, target)

# for GPU, cl_khr_fp16 isn't supported (except now we don't need it!)
# for LLVM, it segfaults because it can't link to the casting function
@unittest.skipIf(getenv("CI", "") != "" and Device.DEFAULT in ["LLVM"], "float16 broken in some CI backends")
class TestHalfDtype(unittest.TestCase):
  def test_half_to_np(self): _test_to_np(Tensor([1,2,3,4], dtype=dtypes.float16), np.float16, [1,2,3,4])
  
  def test_half_to_float(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.float32, [1,2,3,4])
  def test_half_to_int8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.int8, [1,2,3,4])
  def test_half_to_uint8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.uint8, [1,2,3,4])
  def test_half_to_int64(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.int64, [1,2,3,4])

  def test_float_to_half(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.float16, [1,2,3,4])
  def test_int8_to_half(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.float16, [1,2,3,4])
  def test_uint8_to_half(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.uint8), dtypes.float16, [1,2,3,4])
  
  def test_half_add(self): _test_add(Tensor([1,2,3,4], dtype=dtypes.float16), Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.float16, [2,4,6,8])
  def test_half_mul(self): _test_mul(Tensor([1,2,3,4], dtype=dtypes.float16), Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.float16, [1,4,9,16])
  def test_half_matmul(self): _test_matmul(Tensor([[1,2],[3,4]], dtype=dtypes.float16), Tensor.eye(2, dtype=dtypes.float16), dtypes.float16, [[1,2],[3,4]])
  
  def test_half_add_upcast_float(self): _test_add_upcast(Tensor([1,2,3,4], dtype=dtypes.float16), Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.float32, [2,4,6,8])
  def test_int8_add_upcast_half(self): _test_add_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.float16, [2,4,6,8])
  def test_int8_mul_upcast_half(self): _test_mul_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.float16), dtypes.float16, [1,4,9,16])
  def test_half_mul_upcast_float(self): _test_mul_upcast(Tensor([1,2,3,4], dtype=dtypes.float16), Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.float32, [1,4,9,16])
  def test_half_matmul_upcast_float(self): _test_matmul_upcast(Tensor([[1,2],[3,4]], dtype=dtypes.float16), Tensor.eye(2, dtype=dtypes.float32), dtypes.float32, [[1,2],[3,4]])
  def test_int8_matmul_upcast_half(self): _test_matmul_upcast(Tensor([[1,2],[3,4]], dtype=dtypes.int8), Tensor.eye(2, dtype=dtypes.float16), dtypes.float16, [[1,2],[3,4]])

class TestInt8Dtype(unittest.TestCase):
  def test_int8_to_np(self): _test_to_np(Tensor([1,2,3,4], dtype=dtypes.int8), np.int8, [1,2,3,4])
  def test_uint8_to_np(self): _test_to_np(Tensor([1,2,3,4], dtype=dtypes.uint8), np.uint8, [1,2,3,4])
  def test_int64_to_np(self): _test_to_np(Tensor([1,2,3,4], dtype=dtypes.int64), np.int64, [1,2,3,4])

  def test_float_to_int8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.int8, [1,2,3,4])
  def test_float_to_uint8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.uint8, [1,2,3,4])
  def test_float_to_int64(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.int64, [1,2,3,4])

  def test_int8_to_float(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.float32, [1,2,3,4])
  def test_int8_to_uint8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.uint8, [1,2,3,4])
  def test_int8_to_int64(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.int64, [1,2,3,4])

  def test_uint8_to_float(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.uint8), dtypes.float32, [1,2,3,4])
  def test_uint8_to_int8(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.uint8), dtypes.int8, [1,2,3,4])
  def test_uint8_to_int64(self): _test_cast(Tensor([1,2,3,4], dtype=dtypes.uint8), dtypes.int64, [1,2,3,4])

  def test_int8_add(self): _test_add(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.int8, [2,4,6,8])
  def test_int64_add(self): _test_add(Tensor([1,2,3,4], dtype=dtypes.int64),Tensor([1,2,3,4], dtype=dtypes.int64), dtypes.int64, [2,4,6,8])

  def test_int8_mul(self): _test_mul(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.int8), dtypes.int8, [1,4,9,16])
  def test_int64_mul(self): _test_mul(Tensor([1,2,3,4], dtype=dtypes.int64), Tensor([1,2,3,4], dtype=dtypes.int64), dtypes.int64, [1,4,9,16])

  def test_int8_matmul(self): _test_matmul(Tensor([[1,2],[3,4]], dtype=dtypes.int8), Tensor.eye(2, dtype=dtypes.int8), dtypes.int8, [[1,2],[3,4]])
  def test_int64_matmul(self): _test_matmul(Tensor([[1,2],[3,4]], dtype=dtypes.int64), Tensor.eye(2, dtype=dtypes.int64), dtypes.int64, [[1,2],[3,4]])

  def test_int8_add_upcast_float(self): _test_add_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.float32, [2,4,6,8])
  def test_int8_mul_upcast_float(self): _test_mul_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.float32), dtypes.float32, [1,4,9,16])
  def test_int8_matmul_upcast_float(self): _test_matmul_upcast(Tensor([[1,2],[3,4]], dtype=dtypes.int8), Tensor.eye(2, dtype=dtypes.float32), dtypes.float32, [[1,2],[3,4]])

  def test_int8_add_upcast_int64(self): _test_add_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.int64), dtypes.int64, [2,4,6,8])
  def test_int8_mul_upcast_int64(self): _test_mul_upcast(Tensor([1,2,3,4], dtype=dtypes.int8), Tensor([1,2,3,4], dtype=dtypes.int64), dtypes.int64, [1,4,9,16])
  def test_int8_matmul_upcast_int64(self): _test_matmul_upcast(Tensor([[1,2],[3,4]], dtype=dtypes.int8), Tensor.eye(2, dtype=dtypes.int64), dtypes.int64, [[1,2],[3,4]])

  def test_int8_to_uint8_negative(self): _test_op(lambda: Tensor([-1, -2, -3, -4], dtype=dtypes.int8).cast(dtypes.uint8), dtypes.uint8, [255, 254, 253, 252])

  def test_uint8_to_int8_overflow(self): _test_op(lambda: Tensor([255, 254, 253, 252], dtype=dtypes.uint8).cast(dtypes.int8), dtypes.int8, [-1, -2, -3, -4])

if __name__ == '__main__':
  unittest.main()