64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
import ngraph as ng
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import numpy as np
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from tests.runtime import get_runtime
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def test_adaptive_avg_pool():
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runtime = get_runtime()
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input = np.reshape([0.0, 4, 1, 3, -2, -5, -2,
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-2, 1, -3, 1, -3, -4, 0,
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-2, 1, -1, -2, 3, -1, -3,
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-1, -2, 3, 4, -3, -4, 1,
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2, 0, -4, -5, -2, -2, -3,
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2, 3, 1, -5, 2, -4, -2], (2, 3, 7))
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input_tensor = ng.constant(input)
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output_shape = ng.constant(np.array([3], dtype=np.int32))
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adaptive_pool_node = ng.adaptive_avg_pool(input_tensor, output_shape)
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computation = runtime.computation(adaptive_pool_node)
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adaptive_pool_results = computation()
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expected_results = np.reshape([1.66666663, 0.66666669, -3.,
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-1.33333337, -1.66666663, -2.33333325,
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-0.66666669, 0., -0.33333334,
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0., 1.33333337, -2.,
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-0.66666669, -3.66666675, -2.33333325,
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2., -0.66666669, -1.33333337], (2, 3, 3))
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assert np.allclose(adaptive_pool_results, expected_results)
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def test_adaptive_max_pool():
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runtime = get_runtime()
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input = np.reshape([0, 4, 1, 3, -2, -5, -2,
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-2, 1, -3, 1, -3, -4, 0,
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-2, 1, -1, -2, 3, -1, -3,
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-1, -2, 3, 4, -3, -4, 1,
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2, 0, -4, -5, -2, -2, -3,
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2, 3, 1, -5, 2, -4, -2], (2, 3, 7))
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input_tensor = ng.constant(input)
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output_shape = ng.constant(np.array([3], dtype=np.int32))
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adaptive_pool_node = ng.adaptive_max_pool(input_tensor, output_shape)
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computation = runtime.computation(adaptive_pool_node)
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adaptive_pool_results = computation()
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expected_results = np.reshape([4, 3, -2,
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1, 1, 0,
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1, 3, 3,
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3, 4, 1,
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2, -2, -2,
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3, 2, 2], (2, 3, 3))
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expected_indices = np.reshape([1, 3, 4,
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1, 3, 6,
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1, 4, 4,
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2, 3, 6,
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0, 4, 4,
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1, 4, 4], (2, 3, 3))
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assert np.allclose(adaptive_pool_results, [expected_results, expected_indices])
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