/dports/science/nest/nest-simulator-3.1/testsuite/pytests/test_sp/ |
H A D | test_growth_curves.py | 117 self.growth_rate = growth_rate 155 self.growth_rate = growth_rate 198 self.growth_rate = growth_rate 243 self.growth_rate = growth_rate 340 growth_rate = 0.0001 358 tau_ca=tau_ca, beta_ca=beta_ca, eps=eps, growth_rate=growth_rate)) 360 tau_ca=tau_ca, beta_ca=beta_ca, eps=eps, growth_rate=growth_rate)) 381 growth_rate = 0.0001 400 eta=eta, eps=eps, growth_rate=growth_rate)) 420 growth_rate = 0.0001 [all …]
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/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/relay/testing/ |
H A D | densenet.py | 29 def _make_dense_layer(data, growth_rate, bn_size, index): argument 34 relu1, channels=bn_size * growth_rate, kernel_size=(1, 1), name="conv2d_1_%s" % index 39 relu2, channels=growth_rate, kernel_size=(3, 3), padding=(1, 1), name="conv2d_2_%s" % index 44 def _make_dense_block(data, num_layers, bn_size, growth_rate, index): argument 48 layer_out = _make_dense_layer(layer_out, growth_rate, bn_size, "%s_%s" % (index, i)) 63 num_init_features, growth_rate, block_config, data_shape, data_dtype, bn_size=4, classes=1000 argument 82 layer_out = _make_dense_block(layer_out, num_layers, growth_rate, bn_size, i) 83 num_features = num_features + num_layers * growth_rate 135 num_init_features, growth_rate, block_config = specs[densenet_size] 138 num_init_features, growth_rate, block_config, data_shape, dtype, batch_size, classes
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/dports/misc/tvm/incubator-tvm-0.6.1/python/tvm/relay/testing/ |
H A D | densenet.py | 28 def _make_dense_layer(data, growth_rate, bn_size, index): argument 32 conv1 = layers.conv2d(relu1, channels=bn_size * growth_rate, 36 conv2 = layers.conv2d(relu2, channels=growth_rate, kernel_size=(3, 3), 40 def _make_dense_block(data, num_layers, bn_size, growth_rate, index): argument 44 layer_out = _make_dense_layer(layer_out, growth_rate, bn_size, 56 def _make_dense_net(num_init_features, growth_rate, block_config, argument 70 layer_out = _make_dense_block(layer_out, num_layers, growth_rate, bn_size, i) 71 num_features = num_features + num_layers*growth_rate 119 num_init_features, growth_rate, block_config = specs[densenet_size] 121 net = _make_dense_net(num_init_features, growth_rate, block_config,
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/dports/misc/py-tvm/incubator-tvm-0.6.1/python/tvm/relay/testing/ |
H A D | densenet.py | 28 def _make_dense_layer(data, growth_rate, bn_size, index): argument 32 conv1 = layers.conv2d(relu1, channels=bn_size * growth_rate, 36 conv2 = layers.conv2d(relu2, channels=growth_rate, kernel_size=(3, 3), 40 def _make_dense_block(data, num_layers, bn_size, growth_rate, index): argument 44 layer_out = _make_dense_layer(layer_out, growth_rate, bn_size, 56 def _make_dense_net(num_init_features, growth_rate, block_config, argument 70 layer_out = _make_dense_block(layer_out, num_layers, growth_rate, bn_size, i) 71 num_features = num_features + num_layers*growth_rate 119 num_init_features, growth_rate, block_config = specs[densenet_size] 121 net = _make_dense_net(num_init_features, growth_rate, block_config,
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/dports/misc/mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/model_zoo/vision/ |
H A D | densenet.py | 32 def _make_dense_block(num_layers, bn_size, growth_rate, dropout, stage_index): argument 36 out.add(_make_dense_layer(growth_rate, bn_size, dropout)) 39 def _make_dense_layer(growth_rate, bn_size, dropout): argument 43 new_features.add(nn.Conv2D(bn_size * growth_rate, kernel_size=1, use_bias=False)) 46 new_features.add(nn.Conv2D(growth_rate, kernel_size=3, padding=1, use_bias=False)) 85 def __init__(self, num_init_features, growth_rate, block_config, argument 99 self.features.add(_make_dense_block(num_layers, bn_size, growth_rate, dropout, i+1)) 100 num_features = num_features + num_layers * growth_rate 141 num_init_features, growth_rate, block_config = densenet_spec[num_layers] 142 net = DenseNet(num_init_features, growth_rate, block_config, **kwargs)
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/python/mxnet/gluon/model_zoo/vision/ |
H A D | densenet.py | 32 def _make_dense_block(num_layers, bn_size, growth_rate, dropout, stage_index): argument 36 out.add(_make_dense_layer(growth_rate, bn_size, dropout)) 39 def _make_dense_layer(growth_rate, bn_size, dropout): argument 43 new_features.add(nn.Conv2D(bn_size * growth_rate, kernel_size=1, use_bias=False)) 46 new_features.add(nn.Conv2D(growth_rate, kernel_size=3, padding=1, use_bias=False)) 85 def __init__(self, num_init_features, growth_rate, block_config, argument 99 self.features.add(_make_dense_block(num_layers, bn_size, growth_rate, dropout, i+1)) 100 num_features = num_features + num_layers * growth_rate 141 num_init_features, growth_rate, block_config = densenet_spec[num_layers] 142 net = DenseNet(num_init_features, growth_rate, block_config, **kwargs)
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/dports/misc/py-gluoncv/gluon-cv-0.9.0/gluoncv/model_zoo/ |
H A D | densenet.py | 30 def _make_dense_block(num_layers, bn_size, growth_rate, dropout, stage_index, argument 35 out.add(_make_dense_layer(growth_rate, bn_size, dropout, norm_layer, norm_kwargs)) 38 def _make_dense_layer(growth_rate, bn_size, dropout, norm_layer, norm_kwargs): argument 42 new_features.add(nn.Conv2D(bn_size * growth_rate, kernel_size=1, use_bias=False)) 45 new_features.add(nn.Conv2D(growth_rate, kernel_size=3, padding=1, use_bias=False)) 90 def __init__(self, num_init_features, growth_rate, block_config, argument 105 num_layers, bn_size, growth_rate, dropout, i+1, norm_layer, norm_kwargs)) 106 num_features = num_features + num_layers * growth_rate 154 num_init_features, growth_rate, block_config = densenet_spec[num_layers] 155 net = DenseNet(num_init_features, growth_rate, block_config, **kwargs)
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/dports/misc/mxnet/incubator-mxnet-1.9.0/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo/Vision/ |
H A D | DenseNet.pm | 26 func _make_dense_block($num_layers, $bn_size, $growth_rate, $dropout, $stage_index) 32 $out->add(_make_dense_layer($growth_rate, $bn_size, $dropout)); 38 func _make_dense_layer($growth_rate, $bn_size, $dropout) 43 $new_features->add(nn->Conv2D($bn_size * $growth_rate, kernel_size=>1, use_bias=>0)); 46 $new_features->add(nn->Conv2D($growth_rate, kernel_size=>3, padding=>1, use_bias=>0)); 121 …$self->features->add(_make_dense_block($num_layers, $self->bn_size, $self->growth_rate, $self->dro… 122 $num_features += $num_layers * $self->growth_rate; 179 my ($num_init_features, $growth_rate, $block_config) = @{ $densenet_spec{$num_layers} }; 181 $num_init_features, $growth_rate, $block_config,
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/dports/misc/py-mxnet/incubator-mxnet-1.9.0/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo/Vision/ |
H A D | DenseNet.pm | 26 func _make_dense_block($num_layers, $bn_size, $growth_rate, $dropout, $stage_index) 32 $out->add(_make_dense_layer($growth_rate, $bn_size, $dropout)); 38 func _make_dense_layer($growth_rate, $bn_size, $dropout) 43 $new_features->add(nn->Conv2D($bn_size * $growth_rate, kernel_size=>1, use_bias=>0)); 46 $new_features->add(nn->Conv2D($growth_rate, kernel_size=>3, padding=>1, use_bias=>0)); 121 …$self->features->add(_make_dense_block($num_layers, $self->bn_size, $self->growth_rate, $self->dro… 122 $num_features += $num_layers * $self->growth_rate; 179 my ($num_init_features, $growth_rate, $block_config) = @{ $densenet_spec{$num_layers} }; 181 $num_init_features, $growth_rate, $block_config,
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/src/ |
H A D | NonDSparseGrid.cpp | 89 short growth_rate; in NonDSparseGrid() local 96 growth_rate = Pecos::UNRESTRICTED_GROWTH; in NonDSparseGrid() 107 growth_rate = Pecos::MODERATE_RESTRICTED_GROWTH; in NonDSparseGrid() 114 growth_rate, track_colloc, track_uniq_prod_wts); in NonDSparseGrid() 121 growth_rate, track_uniq_prod_wts); in NonDSparseGrid() 128 growth_rate, track_colloc); in NonDSparseGrid() 134 growth_rate); in NonDSparseGrid() 147 short driver_mode, short growth_rate, short refine_control, in NonDSparseGrid() argument 162 ssgDriver->growth_rate(growth_rate); in NonDSparseGrid()
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/dports/science/nest/nest-simulator-3.1/nestkernel/ |
H A D | growth_curve.cpp | 71 double growth_rate ) const in update() 74 …const double z_value = growth_rate * tau_Ca * ( Ca - Ca_minus ) / eps_ + growth_rate * ( t - t_min… in update() 111 double growth_rate ) const in update() 125 const double dz = h * growth_rate * ( 2.0 * exp( -pow( ( Ca - xi ) / zeta, 2 ) ) - 1.0 ); in update() 170 double growth_rate ) const in update() 182 const double dz = h * growth_rate * ( ( 2.0 / ( 1.0 + exp( ( Ca - eps_ ) / psi_ ) ) ) - 1.0 ); in update()
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H A D | growth_curve.h | 57 …update( double t, double t_minus, double Ca_minus, double z, double tau_Ca, double growth_rate ) c… 136 …te( double t, double t_minus, double Ca_minus, double z, double tau_Ca, double growth_rate ) const; 223 …te( double t, double t_minus, double Ca_minus, double z, double tau_Ca, double growth_rate ) const; 295 …te( double t, double t_minus, double Ca_minus, double z, double tau_Ca, double growth_rate ) const;
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H A D | synaptic_element.cpp | 101 def< double >( d, names::growth_rate, growth_rate_ ); in get() 120 updateValue< double >( d, names::growth_rate, growth_rate_ ); in set()
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/pecos/src/ |
H A D | SparseGridDriver.hpp | 45 short growth_rate, short refine_control); 150 short growth_rate = MODERATE_RESTRICTED_GROWTH); 204 void growth_rate(short growth_rate); 206 short growth_rate() const; 316 short growth_rate, short refine_control): in SparseGridDriver() argument 317 IntegrationDriver(BaseConstructor()), growthRate(growth_rate), in SparseGridDriver() 440 inline void SparseGridDriver::growth_rate(short growth_rate) in growth_rate() function in Pecos::SparseGridDriver 441 { growthRate = growth_rate; } in growth_rate() 444 inline short SparseGridDriver::growth_rate() const in growth_rate() function in Pecos::SparseGridDriver
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H A D | LightweightSparseGridDriver.hpp | 42 short growth_rate = MODERATE_RESTRICTED_GROWTH, 97 short growth_rate, short refine_control): in LightweightSparseGridDriver() argument 98 SparseGridDriver(ssg_level, dim_pref, growth_rate, refine_control) in LightweightSparseGridDriver()
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H A D | CombinedSparseGridDriver.hpp | 52 short growth_rate = MODERATE_RESTRICTED_GROWTH, 102 short growth_rate = MODERATE_RESTRICTED_GROWTH, bool track_colloc = false, 390 short growth_rate, short refine_control): in CombinedSparseGridDriver() argument 391 SparseGridDriver(ssg_level, dim_pref, growth_rate, refine_control), in CombinedSparseGridDriver()
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/dports/biology/scrm/scrm-1.7.4/tests/unittests/ |
H A D | test_param.cc | 173 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(0) ); in testParseCommonOptions() 174 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(1) ); in testParseCommonOptions() 175 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(2) ); in testParseCommonOptions() 185 CPPUNIT_ASSERT( areSame(1.5 / 4 / model.default_pop_size(), model.growth_rate(0)) ); in testParseCommonOptions() 197 CPPUNIT_ASSERT_EQUAL( 2.0 / 4 / model.default_pop_size() , model.growth_rate(0) ); in testParseCommonOptions() 198 CPPUNIT_ASSERT_EQUAL( 2.0 / 4 / model.default_pop_size(), model.growth_rate(1) ); in testParseCommonOptions() 199 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(2) ); in testParseCommonOptions() 266 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(2) ); in testParseMergeOptions() 278 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate() ); in testParseMergeOptions() 350 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(0) ); in testParseGrowthOptions() [all …]
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H A D | test_model.cc | 274 CPPUNIT_ASSERT( model.growth_rate(0) == 0 ); in testDebugConstructor() 361 CPPUNIT_ASSERT_EQUAL( 0.0, model.growth_rate(0) ); in testGetters() 364 CPPUNIT_ASSERT_EQUAL( 1.5, model.growth_rate(0) ); in testGetters() 367 CPPUNIT_ASSERT_EQUAL( 1.5, model.growth_rate(0) ); in testGetters() 371 CPPUNIT_ASSERT_EQUAL( 1.0, model.growth_rate(0) ); in testGetters() 375 CPPUNIT_ASSERT_EQUAL( 1.0, model.growth_rate(0) ); in testGetters()
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/dports/graphics/py-urbansim/urbansim-3.2/urbansim/models/ |
H A D | transition.py | 163 def __init__(self, growth_rate, accounting_column=None): argument 164 self.growth_rate = growth_rate 194 nrows = int(round(len(data) * self.growth_rate)) 196 nrows = int(round(data[self.accounting_column].sum() * self.growth_rate)) 199 nrows, self.growth_rate), 246 def _calc_nrows(self, len_data, growth_rate): argument 259 return int(round(len_data * growth_rate))
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/dports/math/cvc4/CVC4-1.7/test/regress/regress0/tptp/ |
H A D | MGT019+2.p | 48 => greater(growth_rate(efficient_producers,T),growth_rate(first_movers,T)) ) )). 82 => greater(growth_rate(efficient_producers,T),growth_rate(first_movers,T)) ) ) ) )).
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/dports/games/openttd/openttd-12.1/src/script/api/ |
H A D | script_town.cpp | 162 uint16 growth_rate; in SetGrowthRate() local 165 growth_rate = 0; in SetGrowthRate() 169 growth_rate = TOWN_GROWTH_RATE_NONE; in SetGrowthRate() 175 growth_rate = std::max(days_between_town_growth * DAY_TICKS, 2u) - 1; in SetGrowthRate() 179 …return ScriptObject::DoCommand(::Town::Get(town_id)->xy, town_id, growth_rate, CMD_TOWN_GROWTH_RAT… in SetGrowthRate() 188 if (t->growth_rate == TOWN_GROWTH_RATE_NONE) return TOWN_GROWTH_NONE; in GetGrowthRate() 190 return RoundDivSU(t->growth_rate + 1, DAY_TICKS); in GetGrowthRate()
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/dports/biology/scrm/scrm-1.7.4/src/ |
H A D | model.cc | 299 void Model::addGrowthRates(const double time, const double growth_rate, in addGrowthRates() argument 301 …addGrowthRates(time, std::vector<double>(population_number(), growth_rate), time_scaled, rate_scal… in addGrowthRates() 319 double growth_rate, const bool &time_scaled, const bool &rate_scaled) { in addGrowthRate() argument 322 if (rate_scaled) growth_rate *= scaling_factor(); in addGrowthRate() 324 growth_rates_list_.at(position).at(population) = growth_rate; in addGrowthRate() 479 os << std::setw(10) << std::right << model.growth_rate(pop); in operator <<()
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H A D | model.h | 140 double growth_rate(size_t pop = 0) const { 172 if (time >= 0 && growth_rate(pop) != 0.0) { 174 pop_size *= std::exp(growth_rate(pop) * (time - getCurrentTime()));
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/dports/math/py-keras-applications/keras-applications-1.0.8/keras_applications/ |
H A D | densenet.py | 93 def conv_block(x, growth_rate, name): argument 109 x1 = layers.Conv2D(4 * growth_rate, 1, 115 x1 = layers.Conv2D(growth_rate, 3,
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/dports/games/openttd/openttd-12.1/src/saveload/ |
H A D | town_sl.cpp | 255 SLE_CONDVAR(Town, growth_rate, SLE_FILE_U8 | SLE_VAR_I16, SL_MIN_VERSION, SLV_54), 256 SLE_CONDVAR(Town, growth_rate, SLE_FILE_I16 | SLE_VAR_U16, SLV_54, SLV_165), 257 SLE_CONDVAR(Town, growth_rate, SLE_UINT16, SLV_165, SL_MAX_VERSION),
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