dtype=np.int32 ) ########### Embedding layer ############## actual = f_el(x) expected = dcnn.e_layer.output(x) assert_matrix_eq(actual, expected, "Embedding") ########## Conv layer ################### actual = dcnn._c_layer_output(x) expected = f_cl(x) assert_matrix_eq(actual, expected, "Conv") ########## Output layer ################### actual = dcnn._p_y_given_x(x) expected = f3(x) assert_matrix_eq(actual, expected, "p_y_given_x") ########## errors ########### actual = dcnn._errors(x, y) expected = f2(x, y) assert_about_eq(actual, expected, "errors") ########## nnl ########### actual = dcnn._nnl(x, y) expected = f1(x, y) assert_about_eq(actual, expected, "nnl")
x = np.asarray(np.random.randint(vocab_size, size=(3, 6)), dtype=np.int32) y = np.asarray(np.random.randint(5, size=3), dtype=np.int32) ########### Embedding layer ############## actual = f_el(x) expected = dcnn.e_layer.output(x) assert_matrix_eq(actual, expected, "Embedding") ########## Conv layer ################### actual = dcnn._c_layer_output(x) expected = f_cl(x) assert_matrix_eq(actual, expected, "Conv") ########## Output layer ################### actual = dcnn._p_y_given_x(x) expected = f3(x) assert_matrix_eq(actual, expected, "p_y_given_x") ########## errors ########### actual = dcnn._errors(x, y) expected = f2(x, y) assert_about_eq(actual, expected, "errors") ########## nnl ########### actual = dcnn._nnl(x, y) expected = f1(x, y) assert_about_eq(actual, expected, "nnl")