import torch
from torch import Tensor
import torch.utils.data.dataloader
from torch import nn
import torch.nn


def arccosh(x):
    """Compute the arcosh, numerically stable."""
    x = torch.clamp(x, min=1 + EPSILON)
    a = torch.log(x)
    b = torch.log1p(torch.sqrt(x * x - 1) / x)
    return a + b


def mdot(x, y):
    """Compute the inner product."""
    m = x.new_ones(1, x.size(1))
    m[0, 0] = -1
    return torch.sum(m * x * y, 1, keepdim=True)


def dist(x, y):
    """Get the hyperbolic distance between x and y."""
    return arccosh(-mdot(x, y))


class EuclideanDistance(nn.Module):
    """Implement a EuclideanDistance object."""

    def forward(self, mat_1: 'Tensor', mat_2: 'Tensor') ->Tensor:
        """Returns the squared euclidean distance between each
        element in mat_1 and each element in mat_2.

        Parameters
        ----------
        mat_1: torch.Tensor
            matrix of shape (n_1, n_features)
        mat_2: torch.Tensor
            matrix of shape (n_2, n_features)

        Returns
        -------
        dist: torch.Tensor
            distance matrix of shape (n_1, n_2)

        """
        _dist = [torch.sum((mat_1 - mat_2[i]) ** 2, dim=1) for i in range(
            mat_2.size(0))]
        dist = torch.stack(_dist, dim=1)
        return dist


def get_inputs():
    return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]


def get_init_inputs():
    return [[], {}]

import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data.dataloader
from torch import nn
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_stack_0(in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 4 % 16
    x0 = xindex % 4
    x2 = xindex // 64
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 4 * x1 + 64 * x2), tmp4 & xmask, other=0.0)
    tmp6 = tl.load(in_ptr1 + (x0 + 4 * x1), tmp4 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp7 = tmp5 - tmp6
    tmp8 = tmp7 * tmp7
    tmp9 = tl.load(in_ptr0 + (16 + x0 + 4 * x1 + 64 * x2), tmp4 & xmask,
        other=0.0)
    tmp10 = tl.load(in_ptr1 + (16 + x0 + 4 * x1), tmp4 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp11 = tmp9 - tmp10
    tmp12 = tmp11 * tmp11
    tmp13 = tmp8 + tmp12
    tmp14 = tl.load(in_ptr0 + (32 + x0 + 4 * x1 + 64 * x2), tmp4 & xmask,
        other=0.0)
    tmp15 = tl.load(in_ptr1 + (32 + x0 + 4 * x1), tmp4 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tmp14 - tmp15
    tmp17 = tmp16 * tmp16
    tmp18 = tmp13 + tmp17
    tmp19 = tl.load(in_ptr0 + (48 + x0 + 4 * x1 + 64 * x2), tmp4 & xmask,
        other=0.0)
    tmp20 = tl.load(in_ptr1 + (48 + x0 + 4 * x1), tmp4 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp21 = tmp19 - tmp20
    tmp22 = tmp21 * tmp21
    tmp23 = tmp18 + tmp22
    tmp24 = tl.full(tmp23.shape, 0.0, tmp23.dtype)
    tmp25 = tl.where(tmp4, tmp23, tmp24)
    tmp26 = tmp0 >= tmp3
    tmp27 = tl.full([1], 8, tl.int64)
    tmp28 = tmp0 < tmp27
    tmp29 = tmp26 & tmp28
    tmp30 = tl.load(in_ptr0 + (x0 + 4 * (-4 + x1) + 64 * x2), tmp29 & xmask,
        other=0.0)
    tmp31 = tl.load(in_ptr1 + (64 + x0 + 4 * (-4 + x1)), tmp29 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp32 = tmp30 - tmp31
    tmp33 = tmp32 * tmp32
    tmp34 = tl.load(in_ptr0 + (16 + x0 + 4 * (-4 + x1) + 64 * x2), tmp29 &
        xmask, other=0.0)
    tmp35 = tl.load(in_ptr1 + (80 + x0 + 4 * (-4 + x1)), tmp29 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp36 = tmp34 - tmp35
    tmp37 = tmp36 * tmp36
    tmp38 = tmp33 + tmp37
    tmp39 = tl.load(in_ptr0 + (32 + x0 + 4 * (-4 + x1) + 64 * x2), tmp29 &
        xmask, other=0.0)
    tmp40 = tl.load(in_ptr1 + (96 + x0 + 4 * (-4 + x1)), tmp29 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp41 = tmp39 - tmp40
    tmp42 = tmp41 * tmp41
    tmp43 = tmp38 + tmp42
    tmp44 = tl.load(in_ptr0 + (48 + x0 + 4 * (-4 + x1) + 64 * x2), tmp29 &
        xmask, other=0.0)
    tmp45 = tl.load(in_ptr1 + (112 + x0 + 4 * (-4 + x1)), tmp29 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp46 = tmp44 - tmp45
    tmp47 = tmp46 * tmp46
    tmp48 = tmp43 + tmp47
    tmp49 = tl.full(tmp48.shape, 0.0, tmp48.dtype)
    tmp50 = tl.where(tmp29, tmp48, tmp49)
    tmp51 = tmp0 >= tmp27
    tmp52 = tl.full([1], 12, tl.int64)
    tmp53 = tmp0 < tmp52
    tmp54 = tmp51 & tmp53
    tmp55 = tl.load(in_ptr0 + (x0 + 4 * (-8 + x1) + 64 * x2), tmp54 & xmask,
        other=0.0)
    tmp56 = tl.load(in_ptr1 + (128 + x0 + 4 * (-8 + x1)), tmp54 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp57 = tmp55 - tmp56
    tmp58 = tmp57 * tmp57
    tmp59 = tl.load(in_ptr0 + (16 + x0 + 4 * (-8 + x1) + 64 * x2), tmp54 &
        xmask, other=0.0)
    tmp60 = tl.load(in_ptr1 + (144 + x0 + 4 * (-8 + x1)), tmp54 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp61 = tmp59 - tmp60
    tmp62 = tmp61 * tmp61
    tmp63 = tmp58 + tmp62
    tmp64 = tl.load(in_ptr0 + (32 + x0 + 4 * (-8 + x1) + 64 * x2), tmp54 &
        xmask, other=0.0)
    tmp65 = tl.load(in_ptr1 + (160 + x0 + 4 * (-8 + x1)), tmp54 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp66 = tmp64 - tmp65
    tmp67 = tmp66 * tmp66
    tmp68 = tmp63 + tmp67
    tmp69 = tl.load(in_ptr0 + (48 + x0 + 4 * (-8 + x1) + 64 * x2), tmp54 &
        xmask, other=0.0)
    tmp70 = tl.load(in_ptr1 + (176 + x0 + 4 * (-8 + x1)), tmp54 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp71 = tmp69 - tmp70
    tmp72 = tmp71 * tmp71
    tmp73 = tmp68 + tmp72
    tmp74 = tl.full(tmp73.shape, 0.0, tmp73.dtype)
    tmp75 = tl.where(tmp54, tmp73, tmp74)
    tmp76 = tmp0 >= tmp52
    tl.full([1], 16, tl.int64)
    tmp79 = tl.load(in_ptr0 + (x0 + 4 * (-12 + x1) + 64 * x2), tmp76 &
        xmask, other=0.0)
    tmp80 = tl.load(in_ptr1 + (192 + x0 + 4 * (-12 + x1)), tmp76 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp81 = tmp79 - tmp80
    tmp82 = tmp81 * tmp81
    tmp83 = tl.load(in_ptr0 + (16 + x0 + 4 * (-12 + x1) + 64 * x2), tmp76 &
        xmask, other=0.0)
    tmp84 = tl.load(in_ptr1 + (208 + x0 + 4 * (-12 + x1)), tmp76 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp85 = tmp83 - tmp84
    tmp86 = tmp85 * tmp85
    tmp87 = tmp82 + tmp86
    tmp88 = tl.load(in_ptr0 + (32 + x0 + 4 * (-12 + x1) + 64 * x2), tmp76 &
        xmask, other=0.0)
    tmp89 = tl.load(in_ptr1 + (224 + x0 + 4 * (-12 + x1)), tmp76 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp90 = tmp88 - tmp89
    tmp91 = tmp90 * tmp90
    tmp92 = tmp87 + tmp91
    tmp93 = tl.load(in_ptr0 + (48 + x0 + 4 * (-12 + x1) + 64 * x2), tmp76 &
        xmask, other=0.0)
    tmp94 = tl.load(in_ptr1 + (240 + x0 + 4 * (-12 + x1)), tmp76 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp95 = tmp93 - tmp94
    tmp96 = tmp95 * tmp95
    tmp97 = tmp92 + tmp96
    tmp98 = tl.full(tmp97.shape, 0.0, tmp97.dtype)
    tmp99 = tl.where(tmp76, tmp97, tmp98)
    tmp100 = tl.where(tmp54, tmp75, tmp99)
    tmp101 = tl.where(tmp29, tmp50, tmp100)
    tmp102 = tl.where(tmp4, tmp25, tmp101)
    tl.store(out_ptr0 + x3, tmp102, xmask)


def call(args):
    arg0_1, arg1_1 = args
    args.clear()
    assert_size_stride(arg0_1, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(arg1_1, (4, 4, 4, 4), (64, 16, 4, 1))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((4, 16, 4), (64, 4, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_stack_0[grid(256)](arg1_1, arg0_1, buf0, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del arg0_1
        del arg1_1
    return reinterpret_tensor(buf0, (4, 4, 4, 4), (64, 16, 4, 1), 0),


def arccosh(x):
    """Compute the arcosh, numerically stable."""
    x = torch.clamp(x, min=1 + EPSILON)
    a = torch.log(x)
    b = torch.log1p(torch.sqrt(x * x - 1) / x)
    return a + b


def mdot(x, y):
    """Compute the inner product."""
    m = x.new_ones(1, x.size(1))
    m[0, 0] = -1
    return torch.sum(m * x * y, 1, keepdim=True)


def dist(x, y):
    """Get the hyperbolic distance between x and y."""
    return arccosh(-mdot(x, y))


class EuclideanDistanceNew(nn.Module):
    """Implement a EuclideanDistance object."""

    def forward(self, input_0, input_1):
        arg0_1 = input_0
        arg1_1 = input_1
        output = call([arg0_1, arg1_1])
        return output[0]
