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removing dependency on setting the Keras backend #79
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@@ -30,7 +30,6 @@ | |
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from gpflow.config import default_float | ||
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tf.keras.backend.set_floatx("float64") | ||
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# %% [markdown] | ||
""" | ||
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@@ -28,8 +28,6 @@ | |
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import gpflux | ||
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tf.keras.backend.set_floatx("float64") | ||
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class LogPrior_ELBO_SVGP(gpflow.models.SVGP): | ||
""" | ||
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@@ -264,15 +262,15 @@ def optimization_step(): | |
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@pytest.mark.parametrize( | ||
"svgp_fitter, sldgp_fitter", | ||
"svgp_fitter, sldgp_fitter, tol_kw", | ||
[ | ||
(fit_adam, fit_adam), | ||
(fit_adam, keras_fit_adam), | ||
(fit_natgrad, fit_natgrad), | ||
(fit_natgrad, keras_fit_natgrad), | ||
(fit_adam, fit_adam, {}), | ||
(fit_adam, keras_fit_adam, {}), | ||
(fit_natgrad, fit_natgrad, {}), | ||
(fit_natgrad, keras_fit_natgrad, dict(atol=1e-7)), | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. this test required lowering tolerance slightly... |
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], | ||
) | ||
def test_svgp_equivalence_with_sldgp(svgp_fitter, sldgp_fitter, maxiter=20): | ||
def test_svgp_equivalence_with_sldgp(svgp_fitter, sldgp_fitter, tol_kw, maxiter=20): | ||
data = load_data() | ||
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svgp = create_gpflow_svgp(*make_kernel_likelihood_iv()) | ||
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@@ -281,14 +279,14 @@ def test_svgp_equivalence_with_sldgp(svgp_fitter, sldgp_fitter, maxiter=20): | |
sldgp = create_gpflux_sldgp(*make_kernel_likelihood_iv(), get_num_data(data)) | ||
sldgp_fitter(sldgp, data, maxiter=maxiter) | ||
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assert_equivalence(svgp, sldgp, data) | ||
assert_equivalence(svgp, sldgp, data, **tol_kw) | ||
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@pytest.mark.parametrize( | ||
"svgp_fitter, keras_fitter, tol_kw", | ||
[ | ||
(fit_adam, _keras_fit_adam, {}), | ||
(fit_natgrad, _keras_fit_natgrad, dict(atol=1e-8)), | ||
(fit_natgrad, _keras_fit_natgrad, dict(atol=1e-6)), | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. this one as well... seems like there was an issue with this one already, so I assumed it might be ok? |
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], | ||
) | ||
def test_svgp_equivalence_with_keras_sequential(svgp_fitter, keras_fitter, tol_kw, maxiter=10): | ||
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didnt try to run this as it needed additional packages