




import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)
class       a__   ( unittest.TestCase				):






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											self.assertEqual(x.component(0      )		,      1      )
											self.assertEqual(x.component(2      )		,      3      )
											__lowerCAmelCase           =	Vector()






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([0, 0, 0, 0, 0, 1]      )
											self.assertEqual(str(_A      )		,      "(0,0,0,0,0,1)"      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3, 4]      )
											self.assertEqual(len(_A      )		,      4      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2]      )
											__lowerCAmelCase           =	Vector([1, 2, 3, 4, 5]      )
											__lowerCAmelCase           =	Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]      )
											__lowerCAmelCase           =	Vector([1, -1, 1, -1, 2, -3, 4, -5]      )
											self.assertAlmostEqual(x.euclidean_length()		,      2.2_36		,      3      )
											self.assertAlmostEqual(y.euclidean_length()		,      7.4_16		,      3      )
											self.assertEqual(z.euclidean_length()		,      0      )
											self.assertAlmostEqual(w.euclidean_length()		,      7.6_16		,      3      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											__lowerCAmelCase           =	Vector([1, 1, 1]      )
											self.assertEqual((x + y).component(0      )		,      2      )
											self.assertEqual((x + y).component(1      )		,      3      )
											self.assertEqual((x + y).component(2      )		,      4      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											__lowerCAmelCase           =	Vector([1, 1, 1]      )
											self.assertEqual((x - y).component(0      )		,      0      )
											self.assertEqual((x - y).component(1      )		,      1      )
											self.assertEqual((x - y).component(2      )		,      2      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											__lowerCAmelCase           =	Vector([2, -1, 4]      )  # for test of dot product
											__lowerCAmelCase           =	Vector([1, -2, -1]      )
											self.assertEqual(str(x * 3.0      )		,      "(3.0,6.0,9.0)"      )
											self.assertEqual((a * b)		,      0      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertEqual(str(zero_vector(1_0      )      ).count("0"      )		,      1_0      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertEqual(str(unit_basis_vector(3		,      1      )      )		,      "(0,1,0)"      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											__lowerCAmelCase           =	Vector([1, 0, 1]      )
											self.assertEqual(str(axpy(2		,      _A		,      _A      )      )		,      "(3,4,7)"      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 0, 0, 0, 0, 0]      )
											__lowerCAmelCase           =	x.copy()
											self.assertEqual(str(_A      )		,      str(_A      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Vector([1, 0, 0]      )
											x.change_component(0		,      0      )
											x.change_component(1		,      1      )
											self.assertEqual(str(_A      )		,      "(0,1,0)"      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											self.assertEqual("|1,2,3|\n|2,4,5|\n|6,7,8|\n"		,      str(_A      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											__lowerCAmelCase           =	[[-3, -1_4, -1_0], [-5, -1_0, -5], [-2, -1, 0]]
											for x in range(a.height()      ):
																for y in range(a.width()      ):
																					self.assertEqual(minors[x][y]		,      a.minor(_A		,      _A      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											__lowerCAmelCase           =	[[-3, 1_4, -1_0], [5, -1_0, 5], [-2, 1, 0]]
											for x in range(a.height()      ):
																for y in range(a.width()      ):
																					self.assertEqual(cofactors[x][y]		,      a.cofactor(_A		,      _A      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											self.assertEqual(-5		,      a.determinant()      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]		,      3		,      3      )
											__lowerCAmelCase           =	Vector([1, 2, 3]      )
											self.assertEqual("(14,32,50)"		,      str(a * x      )      )
											self.assertEqual("|2,4,6|\n|8,10,12|\n|14,16,18|\n"		,      str(a * 2      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											a.change_component(0		,      2		,      5      )
											self.assertEqual("|1,2,5|\n|2,4,5|\n|6,7,8|\n"		,      str(_A      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											self.assertEqual(7		,      a.component(2		,      1      )		,      0.01      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											__lowerCAmelCase           =	Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]		,      3		,      3      )
											self.assertEqual("|2,4,10|\n|4,8,10|\n|12,14,18|\n"		,      str(a + b      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]		,      3		,      3      )
											__lowerCAmelCase           =	Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 1_0]]		,      3		,      3      )
											self.assertEqual("|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"		,      str(a - b      )      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.assertEqual(
											    "|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"		,      str(square_zero_matrix(5      )      )		,      )


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










import hashlib
import unittest

from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_torch_available():
					import torch

if is_vision_available():
					from PIL import Image
else:
					class       a__   :






											@staticmethod
											def     __SCREAMING_SNAKE_CASE(       *_A		,      **_A      ):




																"""simple docstring"""



																pass







def      _a				(						SCREAMING_SNAKE_CASE_							:    Image					):
					__lowerCAmelCase           =	hashlib.mda(image.tobytes()					)
					return m.hexdigest()


@is_pipeline_test
@require_vision
@require_timm
@require_torch
class       a__   ( unittest.TestCase				):
						_a							:   Tuple =   MODEL_FOR_DEPTH_ESTIMATION_MAPPING






						def     __SCREAMING_SNAKE_CASE(       self		,      _A		,      _A		,      _A      ):




											"""simple docstring"""



											__lowerCAmelCase           =	DepthEstimationPipeline(model=_A		,      image_processor=_A      )
											return depth_estimator, [
											    "./tests/fixtures/tests_samples/COCO/000000039769.png",
											    "./tests/fixtures/tests_samples/COCO/000000039769.png",
											]






						def     __SCREAMING_SNAKE_CASE(       self		,      _A		,      _A      ):




											"""simple docstring"""



											__lowerCAmelCase           =	depth_estimator("./tests/fixtures/tests_samples/COCO/000000039769.png"      )
											self.assertEqual({"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )}		,      _A      )
											import datasets

											__lowerCAmelCase           =	datasets.load_dataset("hf-internal-testing/fixtures_image_utils"		,      "image"		,      split="test"      )
											__lowerCAmelCase           =	depth_estimator(
											    [
											        Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"      ),
											        "http://images.cocodataset.org/val2017/000000039769.jpg",
											        # RGBA
											        dataset[0]["file"],
											        # LA
											        dataset[1]["file"],
											        # L
											        dataset[2]["file"],
											    ]      )
											self.assertEqual(
											    [
											        {"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )},
											        {"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )},
											        {"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )},
											        {"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )},
											        {"predicted_depth": ANY(torch.Tensor      ), "depth": ANY(Image.Image      )},
											    ]		,      _A		,      )






						@require_tf
						@unittest.skip("Depth estimation is not implemented in TF"      )
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											pass






						@slow
						@require_torch
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	"Intel/dpt-large"
											__lowerCAmelCase           =	pipeline("depth-estimation"		,      model=_A      )
											__lowerCAmelCase           =	depth_estimator("http://images.cocodataset.org/val2017/000000039769.jpg"      )
											__lowerCAmelCase           =	hashimage(outputs["depth"]      )

											# This seems flaky.
											# self.assertEqual(outputs["depth"], "1a39394e282e9f3b0741a90b9f108977")
											self.assertEqual(nested_simplify(outputs["predicted_depth"].max().item()      )		,      29.3_04      )
											self.assertEqual(nested_simplify(outputs["predicted_depth"].min().item()      )		,      2.6_62      )






						@require_torch
						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											self.skipTest("There is not hf-internal-testing tiny model for either GLPN nor DPT"      )




